WO2015128862A1

WO2015128862A1 - Method and system for providing a user interaction

Info

Publication number: WO2015128862A1
Application number: PCT/IL2015/050208
Authority: WO
Inventors: Moti COHEN
Original assignee: Apester Ltd
Priority date: 2014-02-27
Filing date: 2015-02-25
Publication date: 2015-09-03

Abstract

Disclosed is a computer-implemented method of providing a user interaction, comprising providing a repository that includes a plurality of user interaction types associated with one or more user inputs, each user input being of a user input type that is selected from a group that includes at least a click type and a non-click type, providing content of a web page, providing an interactive window for integrating in the web page which facilitates outputting of at least one of the interactions and facilitates inputting of a respective user input, of the user inputs, associated therewith, wherein at least one of the received user inputs being of the non click type; scanning the content and identifying at least one contextual subject associated with the content.

Description

METHOD AND SYSTEM FOR PROVIDING A USER INTERACTION

TECHNOLOGICAL FIELD

The presently disclosed subject matter relates to the field of online user

interactive activities.

BACKGROUND

The World Wide Web (WWW) is the most accessible source of information available to the public. Anyone with a suitable appliance, such as a personal computer or a mobile appliance, having standard connection to the Internet, may access web pages for the purpose of obtaining content of various subjects included in these web pages. Web pages deliver content to the user in various formats. For example, a web page may display text content, play video or audio, or a combination thereof. The main content in the web page is displayed in a designated place, referred to herein as a main content area.

A common assumption presumes that a viewer of the page, also referred to herein as the user, who is interested in a specific topic, which is the subject of the main content displayed in a web page, may wish to proceed with additional activity related to a particular topic (subject).

Online engagement of a website can be defined as a website's ability to draw and keep a visitor's attention or induce the visitor to interact with the website. Considering the above desire of a user viewing a main content in a web page, online engagement may be aimed at providing the user with a substrate for further interacting with the web page on a specific subject.

Some of the content web pages enable the viewer of the page to interact with the web page by providing an input. A known format, which enables receipt of a user's input, is through a comments box. The comments box is incorporated in a comments area, usually below the main content area including the main content. The user is able to add a comment(s) to the main content through the comments box. A different approach that allows a user to interact with the content of a web page is by referring him to other related articles, (e.g. displaying a list of links to other articles which are assumed to be of interest to the user), or by providing him with advertisements which are assumed to be relevant to the displayed content. However, in both cases, even if the user responds by clicking some of the links of the articles or advertisements, there is no actual interaction with the user, beyond a mere display of additional information to the user, in the form of professional content or advertising.

Yet another effort in this connection is by adding an interactive activity, such as an American Quiz, or a Poll, both of which were once traditionally found only in printed newspapers or magazines. Such interactive activities have been used in the past few years also in online applications. For instance, several entertainment websites provide different kinds of interactive activities for users to complete or in which to participate.

Some websites provide services of adding polls, as an interactive activity, to content websites.

(herein:"Polarb") is an example of such a website. Polarb provides services of adding polls to content websites. The website assumes that publishers that use polls get more contributors than those just using comments (in this connection, 'contributors' can refer to users who contribute information). This means that websites incorporating polls in web pages are more likely to enhance engagement of users with the website (by driving users to participate in the poll) than websites merely displaying a comments area.

Polls, in known methods, can be added anywhere in the web page and are not necessarily adjacent to the main content.

Another issue to consider with when adding polls to a website, is to assess to what extent the type of interactive activity, in this case the poll, actually enhances engagement of the users. That is to say, to determine and/or evaluate how attractive the interactive activity is to the specific user who accesses a particular web page, due to the main content included therein. Current websites integrate polls without consideration of the nature of users or viewers of the main content, with the hope that such polls will enhance engagement of users to the website.

It is therefore desired, according to certain embodiments of the invention, to develop methods for enhancing engagement of users with websites.

GENERAL DESCRIPTION

In accordance with an aspect of the presently disclosed subject matter, there is provided a computer-implemented method of providing a user interaction, comprising:

(i) providing a repository that includes a plurality of user interaction types associated with one or more user inputs; each user input being of a user input type that is selected from a group that includes at least a click type and a non-click type;

(ii) providing content of a web page;

(iii) providing an interactive window for integrating in the web page which facilitates outputting of at least one of the interactions and facilitates inputting of a respective user input, of the user inputs, associated therewith, wherein at least one of the received user inputs being of the non click type;

(iv) scanning the content and identifying at least one contextual subject associated with the content;

(v) determining at least one user interaction type from among the user interaction types that matches the at least one contextual subject according to a subject-interaction matching criterion(a);

(vi) transmitting for outputting through the interactive window at least one user interaction formatted based on the user interaction type that matches the at least one contextual subject; at least one of the determined user interactions type is associated with a user input of the non-click type;

(vii) receiving user input associated with the interaction and being of the non- click type; thed input was fed through the interactive window; and

(viii) performing at least one action related to the received user input. In accordance with an embodiment of the presently disclosed subject matter, there is further provided a computer-implemented method wherein the stage of transmitting for outputting through the interactive window at least one user interaction formatted based on the user interaction type that matches the at least one contextual subject; at least one of the determined user interactions type is associated with a user input of the non-click type, further comprises outputting through the determined interactive window at least one user interaction formatted based on the user interaction type that matches the at least one contextual subject; at least one of the determined user interactions type is associated with a user input of the click type.

In accordance with an embodiment of the presently disclosed subject matter, there is yet further provided a computer-implemented method wherein the subject- interaction matching criterion(a) includes at least one of: interaction-subject history matching degree.

In accordance with an embodiment of the presently disclosed subject matter, there is yet further provided a computer-implemented method wherein the subject- interaction matching criterion(a) further includes at least one of: user history matching degree, interaction history matching degree, and website history matching degree.

In accordance with an embodiment of the presently disclosed subject matter, there is yet further provided a computer-implemented method wherein the action is a non-advertising related action.

In accordance with an embodiment of the presently disclosed subject matter, there is yet further provided a computer-implemented method wherein the non- advertising related action includes providing the user with a second interaction related to the received user input.

In accordance with an embodiment of the presently disclosed subject matter, there is yet further provided a computer-implemented method wherein the action is an advertising related action.

In accordance with an embodiment of the presently disclosed subject matter, there is yet further provided a computer-implemented method wherein the stage of providing a repository that includes a plurality of user interaction types associated with one or more user inputs; each user input being of a user input type that is selected from a group that includes at least a click type and a non-click type, further includes providing a repository that includes one or more advertisements, wherein each of the one or more advertisements is associated with one or more advertisement-labels, and wherein the advertising related action includes: normalizing the user input into one or more labels; selecting one or more advertisements from among the one or more advertisements that reflect a match between the labels and the advertisement-labels associated with the one or more advertisements; and outputting the one or more selected advertisements in the web page.

In accordance with an embodiment of the presently disclosed subject matter, there is yet further provided a computer-implemented method wherein the stage of performing at least one action related to the received user input further comprises updating the subject-interaction matching criterion(a) dependent upon at least the user input.

In accordance with an embodiment of the presently disclosed subject matter, there is yet further provided a computer-implemented method wherein updating the subject-interaction matching criterion(a) includes updating at least one of interaction- subject history value and interaction-subject history weight.

In accordance with an embodiment of the presently disclosed subject matter, there is yet further provided a computer-implemented method wherein updating the subject-interaction matching criterion(a) includes updating at least one of user history value, user history weight, interaction history value, interaction history weight, website history value, and website history weight.

In accordance with an embodiment of the presently disclosed subject matter, there is yet further provided a computer-implemented method wherein the providing in the web page an interactive window for integrating in the web page which facilitates outputting of at least one of the interactions and facilitates inputting of a respective user input, of the user inputs, associated therewith, wherein at least one of the received user inputs being of the non click type, includes integrating in a predefined area in the web page the interactive window. In accordance with an embodiment of the presently disclosed subject matter, there is yet further provided a computer-implemented method wherein the user interaction is selected from a group comprising: a Poll, American Quiz, Open Question, Crossword Puzzle, an Arrow Crossword Puzzle, Anagram and Hangman.

In accordance with an embodiment of the presently disclosed subject matter, there is yet further provided a computer-implemented method wherein the matching degree is determined based on a conversion rate function.

In accordance with an aspect of the presently disclosed subject matter, there is provided a computer-implemented program storage device readable by machine, tangibly embodying a program of instructions executable by the machine to perform a method of providing a user interaction, comprising:

(ii) providing content of a web page;

(v) determining at least one user interaction type from among the user interaction types that matches the at least one contextual subject according to a subject-interaction matching criterion(a); (vi) transmitting for outputting through the interactive window at least one user interaction formatted based on the user interaction type that matches the at least one contextual subject; at least one of the determined user interactions type is associated with a user input of the non-click type;

(vii) receiving user input associated with the interaction and being of thenon- click type; the input was fed through the interactive window; and

(viii) performing at least one action related to the received user input.

In accordance with an aspect of the presently disclosed subject matter, there is yet further provided a computerized device comprising at least one processing unit comprising computer memory operatively connected to at least one processing unit; the at least one processing unit is configured to:

(i) scan content of a web page and identify at least one contextual subject associated with the content;

(ii) determine at least one user interaction type that matches the at least one contextual subject according to a subject-interaction matching criterion(a); wherein the determining of at least one user interaction type is from among a plurality of user interaction types associated with one or more user inputs; wherein each user input being of a user input type that is selected from a group that includes at least a click type and a non-click type; wherein at least one of the determined user interactions type is associated with a user input of the non-click type;

(iii) transmit for outputting through an interactive window for integrating in the web page at least one user interaction formatted based on the determined user interaction type; wherein the interactive window facilitates outputting the at least one of the interactions and facilitates inputting of a respective user input, of the user inputs, associated therewith, wherein at least one of the received user inputs being of the non click type;

(ix) receive user input associated with the interaction and being of the non- click type; the input was fed through the interactive window; and

(iv) perform at least one action related to the received user input. In accordance with an embodiment of the presently disclosed subject matter, there is yet further provided a device wherein the subject-interaction matching criterion(a) includes at least one of: interaction-subject history matching degree.

In accordance with an embodiment of the presently disclosed subject matter, there is yet further provided a device wherein the at least one computer processor is further configured to normalize the user input into one or more labels; select one or more advertisements from among one or more advertisements, wherein each of the one or more advertisements is associated with one or more advertisement-labels, wherein selecting is of one or more advertisements that reflect a match between the labels and the advertisement-labels associated with the one or more advertisements; and output the one or more selected advertisements in the web page.

In accordance with an embodiment of the presently disclosed subject matter, there is yet further provided a device wherein the at least one computer processor is further configured to update the subject-interaction matching criterion(a) dependent upon at least the user input.

In accordance with an aspect of the presently disclosed subject matter, there is yet further provided a computer-implemented computer program product comprising a computer useable medium having computer readable program code embodied therein of providing a user interaction, the computer program product comprising:

computer readable program code for causing the computer to provide a repository that includes a plurality of user interaction types associated with one or more user inputs; each user input being of a user input type that is selected from a group that includes at least a click type and a non-click type;

computer readable program code for causing the computer to provide content of a web page;

computer readable program code for causing the computer to provide an interactive window for integrating in the web page which facilitates outputting of at least one of the interactions and facilitates inputting of a respective user input, of the user inputs, associated therewith, wherein at least one of the received user inputs being of the non click type; computer readable program code for causing the computer to scan the content and identifying at least one contextual subject associated with the content;

computer readable program code for causing the computer to determine at least one user interaction type from among the user interaction types that matches the at least one contextual subject according to a subject-interaction matching criterion(a);

computer readable program code for causing the computer to transmit for outputting through the interactive window at least one user interaction formatted and based on the user interaction type that matches the at least one contextual subject; at least one of the determined user interactions type is associated with a user input of the non-click type;

computer readable program code for causing the computer to receive user input associated with the interaction and being of the non-click type; said input was fed through the interactive window; and

computer readable program code for causing the computer to perform at least one action related to the received user input.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to better understand the subject matter that is disclosed herein and to exemplify how it may be carried out in practice, embodiments will now be described, by way of non-limiting example only, with reference to the accompanying drawings, in which:

Fig. 1 is a functional block diagram schematically illustrating a networking architecture, in accordance with certain embodiments of the invention;

Fig. 2 is a functional block diagram of an interaction providing unit 140 comprised in a general computerized device 150, in accordance with certain embodiments of the invention;

Fig. 3 is a flow diagram showing an example of a sequence of operations performed during interaction matching, in accordance with the presently disclosed subject matter; Fig. 4 is a flow diagram showing a sequence of operations performed during parameter valuation of few exemplary parameters, in accordance with certain embodiments of the invention;

Fig. 5 is a flow diagram showing an example of a sequence of operations performed during advertisement matching, in accordance with the presently disclosed subject matter; and

Fig. 6 is a flow diagram showing an example of a sequence of operations performed during input normalization, in accordance with the presently disclosed subject matter.

DETAILED DESCRIPTION OF EMBODIMENTS

Unless specifically stated otherwise, as apparent from the following discussions, it is appreciated that throughout the specification discussions utilizing terms such as "providing", "outputting", "receiving", "scanning", "identifying", "determining", "performing", updating, normalizing, selecting, integrating, facilitating, transmitting, or the like, include action and/or processes of a computer that manipulate and/or transform data into other data, said data represented as physical quantities, e.g. such as electronic quantities, and/or said data representing the physical objects.

The terms "computer", "computerized device", "machine" or variation thereof should be expansively construed to cover any kind of electronic device comprising or otherwise operatively connected to a computer memory and having data processing capabilities, including, by way of non-limiting example, a personal computer, a server, a computing system, a communication device, a processor (e.g. digital signal processor (DSP), a microcontroller, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), etc.), any other electronic computing device, and or any combination thereof.

As used herein, the phrases "for example, "such as", "for instance" and variants thereof describe non-limiting embodiments of the presently disclosed subject matter. Reference in the specification to "one case", "some cases", "other cases" or variants thereof means that a particular feature, structure or characteristic described in connection with the embodiment(s) is included in at least one embodiment of the presently disclosed subject matter. Thus the appearance of the phrase "one case", "some cases", "other cases" or variants thereof does not necessarily refer to the same embodiment(s).

It is appreciated that certain features of the presently disclosed subject matter, which are, for clarity, described in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features of the presently disclosed subject matter, which are, for brevity, described in the context of a single embodiment, may also be provided in separate embodiments or in any suitable combination or sub-combination of embodiments.

In embodiments of the presently disclosed subject matter, fewer, more and/or different stages than those shown in Figs. 3, 4, 5 and 6 may be executed. In embodiments of the presently disclosed subject matter one or more stages illustrated in Figs. 3, 4, 5 and 6 may be executed in a different order and/or one or more groups of stages may be executed simultaneously. Fig. 1 illustrates a general schematic of the networking architecture in accordance with an embodiment of the presently disclosed subject matter. Functional elements in Fig. 1, 2, 3, 4, 5 and 6 can be made up of a combination of software and hardware and/or firmware that performs the functions as defined and explained herein. Functional elements in Fig. 1, 2, 3, 4, 5 and 6 can comprise at least one respective computer processor and/or computer memory or can be a part of a computer processor or of a computer memory, the computer processor and the memory being configured for executing instructions for performing the respective functions. The network shown in Fig. 1 or various components thereof depicted in Figs. 1 and 2 may comprise fewer, more, and/or different modules than those shown in the figures.

The invention may be described in the general context of computer code or machine-useable instructions, including computer-executable instructions such as program modules, being executed by a computer or other machines, such as other handheld devices. Generally, program modules including routines, programs, objects, components, data structures, and the like refer to codes that perform particular tasks or implement particular abstract data types. Embodiments described herein may be practiced in a variety of system configurations, including hand-held devices, consumer electronics, general-purpose computers, and other specialty computing devices, etc. Embodiments described herein may also be practiced in distributed computing environments where tasks are performed by remote -processing devices that are linked through a communications network.

Each of data repositories 290, 291 and 520 can be configured as integral parts of general computerized device 150 interaction providing unit 140 or configured in a separate storage unit(s) connected (in part or entirely) e.g. over a network communication link to general computerized device 150 interaction providing unit 140. Note that the invention is not bound by the three data repository embodiments. Thus, the data repositories may be consolidated into a single data repository or may be arranged differently as three (or possibly more) repositories. The invention is not bound by any paradigm of organizing data repositories (for instance the relational data base paradigm).

As previously described, a user interested in a specific subject can access a certain web page and obtain content, such as an article or a video, related to that subject. If the web page includes a comment area, the user may, in known systems, add a comment into the generic comment area, by entering free text. If the website contains a poll, in addition to, or instead of the comments area, the user can also participate in the Poll.

However, in known systems, there is no consideration whether the type of the interactive activity, in this case, the poll, matches the preferences or characteristics of the users or viewers of the content displayed in the web page. It can be argued that specific types of interactive activities better match certain characteristics or preferences of certain users, while other types of interactive activities will attract users having other preferences. The nature of users and their preferences can be derived from the content they are viewing in the web page.

For example, viewers of an article relating to education of toddlers would have different characteristics than those of viewers of a heavy metal music video. The latter may, for example, prefer certain types of interactive activities which are different to the kind preferred by the former viewers. The characteristics of the viewers can be derived from the content.

It is therefore desired in accordance with certain embodiments to provide the user with an interactive activity (also to be referred to as "an interaction" or "a user interaction") based on an interaction type which is related to the content accessed by the user.

It should be noted that any reference throughout the description to a main content presumably included in a main area of a web page, is by no way binding. Thus, according to certain embodiments of the subject matter disclosed herein, a user interaction can be associated with any content appearing in a web page, including content that does not form the main content of the web page.

Bearing the above in mind, attention is now drawn to Fig. 1 which is a functional block diagram schematically illustrating a networking architecture, in accordance with the presently disclosed subject matter. The networking architecture in Fig. 1 is an example which demonstrates some general principles of the subject matter disclosed herein and should not be construed as limiting in any way.

Networking architecture 100 includes a general client computerized device 110 operated by a user 130, and one or more web servers such as web server A 102 to web server N 104, all of which communicate via network 120.

For example web server A 102 can be a computerized device implemented as a server computer which may be, but is not limited to, personal or portable computers or a dedicated server-computer which may be characterized by fast CPU, high performance RAM and possibly multiple hard drives and large storage space.

Web server A 102 hosts one or more websites, for example, website A 112. Each website contains one or more web pages. For example, website A 112 contains web page A 106 to web page N 108. Similarly, web server N 104 hosts website N 114 which contains web pages A 116 to web page N 118.

In some embodiments, the number of web servers is scalable and can include any number of web servers accessible over the network 120. Those skilled in the art would readily appreciate that web page A 106 may be hosted on different web servers, and different portions of a single web page can, in practice, be hosted on different servers.

According to the presently disclosed subject matter, user 130 wishes to obtain content and accesses web page A 106, included in website A 112, by using general computerized device 110.

Network 120 may be based on any type of communication network or any combination of different types of networks. For example, network 120 can be realized by way of example over any one of the following networks: the Internet, a local area network (LAN), wide area network (WAN), metropolitan area network (MAN), any type of telephone network (including for example PSTN with DSL technology) or mobile network (including for example GSM, GPRS, CDMA etc.) or any combination thereof. Communication in the network can be realized through any suitable connection (including wireless, landline, cable line, fiber-optic line, etc.) and communication technology or standard (WiFi, 3G, LTE, etc).

Note that Website A 112 can be dedicated to a specific subject. Alternatively, website A 112 can be a general website relating to various subjects, each covered by one or more web pages of website A 112.

Content of diverse formats, for example, multimedia content such as video or audio, or text content, images, or any combination thereof can be provided in web page A 106. In addition to content, advertisements, various purpose banners, self-promotions, fillers, references to other articles, and the like can also be provided in web page A 106.

An interactive window (not shown) for integrating in web page A 106 is also provided. The interactive window facilitates outputting of at least one of said interactions and facilitates inputting of a respective user input, which is associated with the interaction.

General computerized device 150 included in networking architecture 100, is operatively connected to network 120 for accessing web page A 106. General computerized device 150 comprises interaction providing unit 140. Interaction providing unit 140 is configured to communicate with network 120 through computerized device 150. Interaction providing unit 140 is configured to scan provided content of web page A 106, and to identify at least one contextual subject associated with the content of web page A 106.

Based on the identified contextual subject, interaction providing unit 140 is further configured to determine at least one user interaction type from among several types of user interactions and to output a formed user interaction based on the determined type of user interaction. Interaction providing unit 140 is configured to transmit for outputting, through the interactive window, the at least one user interaction.

The determination of an interaction type to match an identified subject is according to subject-interaction matching criterion(a).

After the user inserts an input to the interaction, which is associated with the interaction, interaction providing unit 140 is configured to receive user input which was fed though the interaction window, and perform at least one action related to the received user input.

Before moving on and for better clarity, consider the following non-limiting example. Text content of web page A 106, such as an article, is provided. Interaction providing unit 140 scans the content and identifies that the article is related to a certain cultural event. While considering three possible interaction types: American Quiz, a Poll and an Open Question, based on the identified subject of the cultural event, interaction providing unit 140 determines that American Quiz is the interaction type, out of the three possible choices, to be output in web page A 106. American Quiz was determined to match the identified subject cultural event based on subject-interaction matching criterion(a), which will be further discussed below.

Interaction providing unit 140 then selects a formed American Quiz (which was formed (in advance) on a certain subject, e.g. the cultural event) and transmits, for outputting, the formed American Quiz in interactive window integrated in web page A 106.

The user inserts an input by selecting one choice of the presented choices of the American Quiz. Interaction providing unit 140 is configured to receive the user's choice which was fed through the interactive window, and perform another action related to the user's selection. For example, Interaction providing unit 140 transmits a second interaction to be output through the interactive window to the user, such as a Poll having content which is related to the user's selection in the American Quiz.

It should be noted that the invention is neither bound by the structure of architecture network depicted in Fig. 1, nor by the functionalities and structure of each of the various units. It should be noted that the above description illustrates certain embodiments of the invention only. Thus, those skilled in the art would readily appreciate that one or more actions performed in interaction providing unit 140 can alternatively or additionally, also be performed in general computerized device 110 or in one or the web servers, such as web server A 102. For example, scanning content of web page A 106 can be performed in certain cases in interaction providing unit 140, however, in other cases, it can be done in web server A 102 or on a copy of the content of web page A 106, as received by general computerized device 110. Another non- limiting example refers to the interactive window. In some cases, the interactive window or a basic form thereof can be formed in a copy of web page A 106 stored in general computerized device 110. The user interaction can then be output in the interactive window. Alternatively or additionally, the interaction window, a basic form thereof or an element integrated in the webpage enabling to add interactive window into the window can be formed in web page A 106 stored in web server A 102.

Further details of interaction providing unit 140 are illustrated below with respect to Fig. 2.

Fig. 2 is a functional block diagram of an interaction providing unit 140 comprised in general computerized device 150, in accordance with certain embodiments of the invention.

Interaction providing unit 140 includes semantic engine 210, interaction matching engine 220 operatively coupled to parameter data repository 290 and interaction data repository 291, interaction injector 240, user input receiver and handler 250 and parameter updating engine 260.

It should be noted that all elements of interaction providing unit 140 are configured to communicate with network 120 and/or transmit and receive data through network 120. Interaction providing unit 140 can access web page A 106 through general computerized device 150. Web page A 106 contains content 270, and further includes an interactive window 280. As previously depicted, the above illustration is exemplary only. In some cases, interaction providing unit 140 is configured to access or receive provided copy of content of web page A 106. Additionally, in some cases, interactive window 280 for integrating in web page A 106 is also provided.

Semantic engine 210 is configured to access web page A 106 in order to scan content 270. According to the presently disclosed subject matter, semantic engine 210 can use known programming tools, such as natural programming tools (NLP), image recognition tools, video recognition tools and audio recognition tools, for scanning content of different formats, in order to scan content 270 of web page A 106. Semantic engine 210 can scan any format of content 270, including text, video, audio, or a combination thereof.

According to certain embodiments, the output of the above scanning tools such as the NLP tools can be used as is to identify at least one contextual subject associated with the content 270. For example, in case of text content, semantic engine 210 is configured to receive from the programming tools a list of labels representing words and the number of times that each of the words appears in the content. In some case, semantic engine 210 identifies the contextual subject as the label (word) having the largest number of appearances in the text. Alternatively or additionally, the output can further be processed, e.g. by semantic engine 210, in order to identify a more specific contextual subject. For example, semantic engine 210 can compare the list of labels to an internal data base which stores previously identified contextual subjects and select one of the labels having a match to a stored contextual subject. Another example of processing the output is to define a contextual subject matter based on a combination of two or more labels and/or ignore labels having a small number of appearances in the context. Those skilled in the art would readily appreciate that many methods for processing the output can also be performed in order to identify a basic or a more specific contextual subject.

Once content 270 is scanned, at least one contextual subject associated with the content 270 is identified. The term "subject" should broadly be interpreted to refer to general fields of interest, a predominant theme, or a topic of the scanned content. Some examples are News, Economics, Culture, Sports, and the like.

Alternatively to identifying one subject, semantic engine 210 identifies more than one subject associated with the content, and returns a list containing all identified subjects, possibly sorted according to a predetermined criterion, such as the most dominant subject of the scanned content.

In some examples, the subjects can form a general category comprising more specific sub-categories (or sub- subjects). For example, the category of News can contain two sub-categories of National News and International News. Thus, semantic engine 210 is configured to identify one or more general categories, and one or more sub-categories included in each of the one or more general categories. Similarly to above, the results can be sorted, based on a predetermined criterion.

Note that the invention is not bound by these examples of identifying subject(s).

According to the presently disclosed subject matter, subsequent to identifying at least one contextual subject, interaction matching engine 220 determines at least one interaction type that matches the identified contextual subject, from among a plurality of user interaction types. The plurality of user interaction types can be stored in interaction data repository 291, operatively coupled to interaction matching engine 220.

The determination of the interaction type that matches the identified contextual subject is according to subject-interaction matching criterion(a). For example, matching criterion(a) can include the matching degree of an interaction type when considering one or more parameters, i.e., the matching degree is determined based on one or more parameters. These parameters can be stored in parameter data repository 290. Further details of interaction matching engine 220, data repositories 290 and 291 and subject- interaction matching criterion(a) are further discussed below with reference to Figs. 3 and 4.

As will be further exemplified in Figs. 3 and 4 and with reference to the above example of identified subject of cultural event, American Quiz interaction type is determined to be a matching interaction to the cultural event, as it has a prevailing subject-interaction matching criterion(a) over the Poll and the Open Question. In case more than one contextual subject is identified in content 270 by semantic engine 210, or in case a generic subject and associated specific sub-subjects have been identified, in accordance with certain embodiments, interaction matching engine 220 determines one interaction type per identified subject or sub-subjects, according to subject-interaction matching criterion(a). In certain embodiments, the same interaction type can be determined as matching for different identified subjects.

Note that the invention is not bound by the specified examples of matching interaction type or types to a subject or subjects.

Bearing this in mind, after at least one type of user interaction has been determined, an interaction, of the determined type of user interactions, is formed or obtained (should it have been formed in advance) by interaction matching engine 220.

Before moving on, it should be noted that interactions are built and stored in advance and used (later) during the process of matching interactions to content. Thus, interaction matching engine 220 is configured to provide, in advance, an interaction template, associated with any interaction type, to an author of content 270 or any other entity for forming the interaction, i.e., by inserting content into the interaction template and converting the generic template of an interaction type into a formed interaction of a certain type, including content. This means that a formed interaction exists for one or more interaction types, for one or more subjects. In a non-limiting example, in a culture subject, a formed interaction is stored for American Quiz, Open Question and a Poll. Upon determining that American Quiz matches Cultural event, interaction matching engine 220 selects the formed American Quiz interaction.

In certain embodiments, the formed interactions can be stored in interaction data repository 291.

Interaction matching engine 220 is configured to forward the (in advance) formed interaction to interaction injector 240 for transmitting for outputting the formed interaction in web page A 106.

In accordance with certain embodiments, in case there is more than one determined interaction type, interaction matching engine 220 is able to form a respective interaction for each of the determined interaction types, possibly based (in advance) on formed interactions.

Interaction injector 240 can then insert the one or more formed user interactions, into web page A 106. The interaction is output through interactive window 280 included in web page A 106. As previously depicted, alternatively or additionally, interaction injector 240 is configured to transmit the interaction for outputting, through interactive window 280.

In case more than one user interaction has been formed, interaction injector 240 is configured to insert the one or more user interactions into interactive window 280. Note that the insertion of the interaction to the interactive window is performed in a known per se manner. For example, the insertion of the interaction can use known HTML Iframes which enables displaying a web page (e.g. an interactive window) within a web page (e.g., a web page including content).

Interactive window 280 can be positioned in web page A 106 in several areas of the web page. In some examples, interactive window 280 can follow content 270 and can be positioned at the end of content 270, as exemplified in Fig. 2. In some other examples, where content 270 is text format, interactive window 280 can be incorporated inside content 270, for instance, in the middle of an article, or in another selected position. Yet, in some other examples, interactive window 280 can be provided in a different, second web page (not shown). A second web page can be designated, for example, to social community activities. In such cases, web page A 106 can contain a link or any format of a reference to the second web page. Following a user link of the reference, the user is directed to the second web page, possibly exactly to the position of the interactive window 280 in the second web page.

According to certain embodiments of the disclosed subject matter, after outputting through interactive window 280 at least one user interaction, the user provides an input, for example, by participating in the interaction.

The user's input to the interaction is fed through the interactive window, and is received e.g. by user input receiver and handler 250, that is also included in interaction providing unit 140. The user input is associated with the interaction and can be of different types, as further explained below.

Input receiver and handler 250 is configured to receive the user input which can be received in different formats such as free text, drag & drop or clicking (when selecting an option). The different formats are handled e.g. by normalizing them to one or more known per se label based formations. The formatted labels can be used for extracting data, for example, relating to the user's preferences or content profiling. Further details of handling and normalizing the user input are disclosed with respect to Figs. 5 and 6.

According to certain embodiments of the presently disclosed subject matter, in response to receiving the user's input, at least one action is performed. The action is related to the received user input.

One example of an action which is performed with respect to the received user input is providing the user with additional content, such as an advertisement. The advertisement can be selected based on the user input. This action can be referred to as an advertisement related action. Further details of this action are disclosed below with respect to Figs. 5 and 6.

Another example of an action related to the received user input is providing the user with an additional content interaction that matches the identified contextual subject according to a subject-interaction matching criterion(a). This type of action can be referred to as a non-advertising related action.

In certain embodiments, following receipt of user input, for example participation in an interaction, the parameters in parameter data repository 290 can be updated, based on such user input. For example, a user history parameter can be updated to refer to current input and to reflect that the user is interested in the specific interaction type for which he provided input.

Once a user input is received, the formatted labels of the user input can be indicative of the user's preferences or content profiling. Based on the user preferences or content profiling, an additional user interaction can be provided to the user. Additional user interaction can be obtained in a similar way to that discussed above with respect to determining a first user interaction that matches the identified contextual subject. Alternatively, the additional interaction type can be determined, for example, based on additional contextual subjects identified by semantic engine 210, or by different consideration of the parameters for determining the matching interaction. Further details of parameters and the utilization thereof for calculation of the subject interaction matching criterion(a), as well as updating them, are illustrated below with reference to Figs. 3 and 4.

Any piece of information provided to the user, such as an advertisement or an additional interaction, can be transmitted for outputting in interactive window 280, instead of the first interaction provided to the user. Alternatively, the piece of information can be output in a second interactive window (not shown), or can be output in another area of web page A 106 or the second web page (if the first interaction was provided in a second web page).

Once user input is received, in certain embodiments, parameter updating engine 260 is configured to update parameters included in parameter data repository 290 in accordance with the received input. Further details of updating the parameters are disclosed with respect to Fig. 3 and 4.

It should be noted that the invention is neither bound by the structure of interaction providing unit 140 or computerized device 150 depicted in Fig. 2, nor by the functionalities and structure of each of the various units.

Turning now to Fig. 3, this illustrates a flow diagram showing an example of a sequence of operations performed during interaction matching, in accordance with the presently disclosed subject matter. As discussed with respect to Fig. 2 above, semantic engine 210 is configured to scan content of web page A 106 to identify one or more contextual subjects. After at least one contextual subject associated with the content is identified, interaction matching engine 220 determines at least one user interaction type, from among a plurality of user interaction types stored in interaction data repository 291, that matches the at least one contextual subject, according to a subject-interaction matching criterion(a). For example, matching criterion(a) can include the matching degree of an interaction type when considering one or more parameters.

It should be noted that the term "criterion(a)" as used herein should be expansively construed to include any compound criterion, including, for example, several criteria and/or their logical combinations.

Interaction data repository 291 is configured to store a plurality of user interaction types such as the examples of interaction types in Fig. 3: open question 301, Poll 302 and American Quiz 303. Some additional non-limiting examples of interaction types are a crossword puzzle, an arrow crossword puzzle, an Anagram, and Hangman (wheel of fortune).

Each of the interaction types can be referred to by indication only in interaction data repository 291, such as a name identifying the interaction type. Alternatively or additionally, interaction data repository 291 is configured to store one or more formed interactions associated with each of the interaction types, for one or more subjects.

Each of the interaction types, such as interaction types 301-303, is designated to receive a certain input from the user, which is correlated with the interaction type. For example, user's input to an open question is typed text or other symbols by using input means that are included in a user's computerized device, such as a keyboard, or by using a virtual keyboard provided to the user. User's input to a Poll or to an American Quiz, on the other hand, can be selection of one of the options presented to the user. Other types of input are also possible, such as dragging items of an interaction with a mouse operated by the user on his computerized device.

The interaction types can therefore be defined in terms of the user input which is received in the interaction.

Some types of interactions can require a number of clicks of the user in order to receive user input. This type can be referred to as a "non-click type" interaction. One example of such a "non-click type" interaction type is an open question, in which the user is required to type text or symbols to provide input to the interaction. The text can be inserted for example by the user keyboard or by a virtual keyboard provided to him (where the user input is fed as a succession of clicks). Other types of non-click interactions are for example a crossword puzzle, an arrow crossword puzzle, an Anagram, and Hangman (wheel of fortune), where the user inputs include filling in the puzzles by typing answers, suggesting a word for an anagram word or to a missing- letters word, by typing a suggested word/letter.

Another user input type interaction can be referred to as a "click type" interaction. Such click type interactions require a single click of the user in order to receive the user input. Examples of such click type interactions include a Poll and an American Quiz. In both of these examples, a selection of the answer (in an American Quiz) or the option (among two or more options displayed to the user) by the form of a single click enables the user to participate in the interaction and form a user input.

According to certain embodiments of the disclosed subject matter, interaction data repository 291 includes a plurality of user interactions, associated with user inputs, each user input being of a type that is selected from a group that includes at least a click type and a non-click type.

Referring to Fig. 2, interactive window 280 provided for integrating in web page A 106 facilitates outputting of at least one of the interactions and facilitates inputting of respective user input (all in a known per se manner, where the type of user input can be defined as either a click type or a non-click type).

Reverting now to Fig. 3, according to certain embodiments of the presently disclosed subject matter, determination of the interaction type that matches the identified contextual subject is according to subject-interaction matching criterion(a). For example, matching criterion(a) can include the matching degree of an interaction type when considering one or more parameters, i.e., the matching degree (also referred to as the score of an interaction type) is determined based on one or more parameters stored in parameter data repository 290.

The subject-interaction matching criterion(a) can be determined by interaction matching engine 220. Interaction matching engine 220 is configured to receive, as input, the identified subject and to determine, based on one or more parameters of the parameters set, the matching degree (score) of one or more interaction types. Once a matching degree has been calculated for one or more interaction types, interaction matching engine 220 is configured to select, based on the matching degree, one or more, and, among these interaction types, the interaction type that matches the identified subject. In one case, the interaction type having the highest matching degree (score) is selected as a matching interaction.

The parameter set comprising one or more parameters can be stored in parameter data repository 290. Parameter data repository 290 can be updated with new parameters at any time. Some non-limiting examples of parameters are further illustrated with respect to Fig. 4.

According to certain embodiments, each of the parameters has a value. Values are calculated according to a certain function, such as the conversion rate function explained below. A score of an interaction type is calculated based on a parametric function. One example of a parametric function is summing all calculated values of all parameters.

As explained, the score of an interaction type represents the matching degree of the interaction type to an identified subject, which can be used as subject-interaction matching criterion(a).

In some embodiments, each of the parameters is given a weight. The weight reflects the desired influence of the parameter's value on the aggregated result, compared to other parameters in the set. The weights can be set independently of the values of the parameters. Alternatively, the weights can be set in consideration of the parameters' values, for example, if a certain predefined threshold has been met. In a non-limiting example, if, according to the user history parameter, the user strongly favors a certain type of interaction, the parameter of user history (which indicates the user's preferences) may be given a high weight. Yet, in another case high weight can be given to the destination parameter, e.g., if it appears that the audience (users) of a certain website strongly prefers a certain type of interaction.

If parameters are given weights, then the score of the interaction type is calculated based upon a parametric weighing function. In such cases, each value is multiplied by its respective weight. After calculating the parameters according to their weights, the score of the interaction type can be calculated based on a parametric function, for example by summing the values of one or more parameters (after these values have been multiplied by their respective weights).

In certain embodiments, default values and/or weights can be set to parameters. For example, the value of user history parameter of a new user can be set with a default '0' value, such that when calculating the parameters to determine a matching interaction, the parameter of user history is not considered. Default values can later be updated.

In some other embodiments, the values and/or weights can automatically be updated when certain conditions are met. For example, the values and/or weights can be updated after receipt of a user input.

It should be noted that the invention is neither bound by the sequence of operations performed during interaction matching depicted in Fig. 3, nor by the functionalities and structure of each of the various units referred to in Fig. 3.

Fig. 4 illustrates a flow diagram showing a sequence of operations performed during parameter valuation of a few exemplary parameters, in accordance with certain embodiments of the invention.

Interaction matching engine 220 is configured to determine the matching degree of one or more interaction types to at least one identified subject. It should be noted that the process illustrated in Fig. 4 relates to determining the matching degree of a single type of interaction, with respect to a single identified subject. The process of Fig. 4 ends by scoring (illustrated as decision 450) one interaction type for a given identified subject. The score of an interaction type represents the matching degree of the interaction type to the identified subject. In certain embodiments, after one or more interaction types are scored, interaction matching engine 220 is configured to select the interaction type having the highest score.

In case more than one interaction type should be considered in a single identified subject, the process of scoring an interaction type has to be implemented for each of the interaction types.

If more than one subject has been identified, interaction matching engine 220 is configured to implement the process illustrated in Fig. 4, with respect to each of the identified subjects. In each of the subjects, interaction matching engine 220 is configured to implement the process illustrated in Fig. 4 with respect to each of the interaction types that need to be considered in each of the identified subjects.

More specifically, in the process illustrated in Fig. 4, interaction matching engine 220 receives, as an input, an identified subject. Once an identified subject has been received, interaction matching engine 220 calculates the score of one or more interaction types. For each of the interaction types, interaction matching engine 220 calculates the value of one or more parameters included in parameter data repository 290. The score of the interaction type can then be determined based on a parametric function considering the values of the parameters. If weights are assigned to the parameters, then each of the values of the parameters, in certain embodiments, is multiplied by its respective weight.

Fig. 4 illustrates some examples of parameters. One of ordinary skill in the art would realize that fewer or additional parameters may also be included in the parameters set.

The set of parameters included in parameter data repository 290 includes the following exemplary parameters: user history 410, interaction history 420, interaction- subject history 430 and website history 440. A non-limiting example of an additional parameter, (not shown in Fig. 4), is the last input or lack of input of the user to a certain interaction.

Each of the parameters 410-440 has a value and a respective weight. In this example, the values are calculated according to a conversion rate function further explained below. Each calculated value is then multiplied by its respective weight. The score of the interaction type is then calculated based on summing the values of all parameters which have been multiplied by respective weights.

"Conversion rate" often can be defined as the rate of converting site visitors into paying customers, although different sites may consider a "conversion" to be some sort of result other than a sale. One example of a conversion event other than a sale is if a visitor to the site takes an action beyond a casual content view or website visit, such as clicking on a banner or a link. For example, on News websites, a successful conversion can refer to a membership registration or newsletter subscription.

With respect to the subject matter disclosed herein, the term "conversion" can generally refer to receipt of a user input to a displayed interaction, i.e., the number of times that a user input to an interaction was received, divided by the total number of times that a user was provided with an interaction. This value can be referred to as an "input-interaction" pair.

Alternatively or additionally, the conversion rate can be calculated with respect to a specific subject ("subject-input-interaction"). Examples of both conversion rates are detailed below.

Put simply for clarity only, the more the user interacts with outputted interactions by feeding appropriate inputs, the higher the conversion rate. The lesser the user interacts with the interactions (e.g. by ignoring the interaction and not providing an input thereto) the lower the conversion rate. The user's act of interacting with a user interaction can be referred to as the user participating in the interaction, e.g., the user filling in an answer to an open question, selecting an answer in a quiz or voting in a poll. Leaving the interaction uncompleted, and possibly, leaving the web page by closing it, is considered as a lack of input of the user., and will obtain a lower the conversion rate.

As explained, the process illustrated in Fig. 4 refers to scoring a single interaction type. Hence, each of the interaction types has a corresponding set of parameters having certain values and possibly certain weights. The values and the weights can be different in each of the interaction types. On the other hand, in some cases, different types of interactions can have some or all identical values and/or weights.

The first exemplary parameter is user history 410. User history can generally refer to the history actions of the user. The value of the user history 410 can refer to the conversion rate of the user with a specific type of interaction, i.e., the number of appearances of a certain interaction type to the user to which the user provided an input, divided by the total number of appearances of the certain interaction type to the user. The conversion rate is illustrated in the equation below:

CR user history- A'u (U, INT) / A (U, INT)

where:

CR- represents 'conversion rate' ;

A (U, INT)- represents number of appearances of interaction type INT to user U; and

A'u (U, INT)- represents number of appearances of interaction type INT to user U, in which user U provided an input.

In the above equation, the conversion rate refers to a specific user, a specific interaction type and an input provided by the specific user to that type of interaction ("input-interaction" pair).

Alternatively or additionally, the conversion rate can be calculated with respect to a specific contextual subject to which the interaction was associated in a particular appearance ("subject-input-interaction"), i.e.:

CR user history- A's_, u (U, INT) / As (U, INT)

where:

CR, A(U, INT) and A'(U, INT) are as above, and

S refers to a certain subject.

To exemplify the above, user history (of "input-interaction" conversion rate) can refer to the number of times that the user provided an input to the American Quiz divided by the number of times that American Quiz was displayed to a user. Alternatively or additionally, user history (of the "subject-input-interaction "conversion rate) can refer to the number of times that the user provided his input to an American Quiz when followed a Cooking video (the cooking stands for the "subject") divided by the number of times that American Quiz was determined to be matched to Cooking content and was displayed to the user, after a video relating to Cooking. The user history can be stored for example in a cookie located in the computer device of the user, e.g. in the general computerized device 110 as illustrated in Fig. 1. Another alternative is that the information of user history is stored in parameter data repository 290. Note that the invention is not bound by these examples.

Note also that the user may be required to register, e.g., by registering web page A 106, to enable identification of the user and extraction of any relevant information relating to the user history conversation rate or any other relevant information.

The arrows 411 and 412 appearing in Fig. 4 refer to two types of users and emphasize that in case the user is a first time user (arrow 411), no consideration of user history is made. If, on the other hand, the user is a returning user (arrow 412), it is assumed that the system has some information on the user and can consider it as a parameter.

Other exemplary parameters are interaction history 420 and interaction-subject history 430 which refer to the conversion rate of the interaction in general, and the conversion rate of the interaction with respect to a specific contextual subject, respectively. Interaction history 420 refers to the history appearances of an interaction of a certain type. The value of interaction history 420 is the conversion rate of the number of instances of the interaction displayed to all users in which a user input was provided, divided by the total number of instances of the interaction to all users.

Interaction-subject history 430 refers to interaction history relating to a certain subject. Meaning, the value of interaction-subject history 430 is the conversion rate of the number of instances of the interaction displayed to all users viewing content identified as relating to a certain subject, and in which a user input was provided, divided by the total number of instances of the interaction displayed to all users viewing content identified as relating to a certain subject.

Destination history 440 refers to the interaction types appearing in a specific website, for example, website A 112 included in Fig. 1. The value of destination history is the conversion rate of the total number of appearances of a certain interaction type in a specific website, in which a user input was provided, divided by the total number of appearances of a certain interaction type in the website. As explained above, these are merely illustrating examples. In accordance with certain embodiments, fewer or additional parameters may be considered.

In accordance with certain embodiments, the value of each of the parameters can be calculated, based on a function other than a conversion rate. Thus, retention rate is another example of a calculating function of the value of parameter user history. In retention rate, the value of the user history is determined based on one or more of the following: the total number of interactions in which the user participated, the number of visits of the user to the website, the number of actions of the user per page, etc.

In accordance with certain embodiments, a combination of one or more calculating functions is also possible for determining the score of an interaction type.

In accordance with certain embodiments, the values of each parameter can be calculated based on a different function.

Bearing this in mind, after interaction matching engine 220 calculates the parameter values (e.g. in accordance with the parameter value calculation discussed above), and possibly applies respective weights to each parameter, interaction matching engine 220 calculates a score for a given interaction type (illustrated in Fig. 4 as decision 450). The score of an interaction type represents the matching degree of the interaction type to an identified subject.

The process of scoring an interaction type is performed for each of the selected interaction types which are candidates for matching to certain content. By one embodiment, all the interaction types that are stored in data repository 291 are valid candidates. Alternatively, interaction matching engine 220 can select only one or some of the stored types as candidates. For example, interaction matching engine 220 can select only the last two interaction types, to which the user provided an input. The invention is not bound by these examples.

Moving on, once a score has been calculated for each of selected types of interactions, interaction matching engine 220 is configured to determine at least one user interaction type from among selected user interaction types, that matches at least one identified contextual subject, according to a subject-interaction matching criterion(a). In certain embodiments, matching criterion(a) can include the matching degree of an interaction type. Hence, interaction matching engine 220 is configured to select the interaction type having the highest score, representing the matching degree of the interaction type.

To demonstrate the above, the following example is presented. Consider two interaction types: an Open Question and an American Quiz. The contextual subject that was identified (e.g. by semantic engine 210) in the content of a website is Sports. Consider two parameters in the system: user history and interaction-subject history (referenced as 410 and 430 in Fig. 4).

The values of the parameters are calculated (e.g. by interaction matching engine 220) based on a conversion rate and are depicted below:

As noted from the above table, 50% of the times that Open Question was displayed to the user, the user provided an input (answered the question), whereas 90% of the times that American Quiz was displayed to the user, the user provided an answer. The opposite percentages were calculated when considering the interaction-subject history parameter.

The weighting function sets the default weights to be equal in all parameters, unless the value of user history parameter in a certain interaction type exceeds 80%, in which case the weight will be 0.8 and the remaining percentages will be equally divided between the other parameters. Hence, the weight given to American Quiz is 0.8 and to Open Question 0.2.

The calculated score for each of the interaction types for Sports, is as indicated in the last row. In the above example, American Quiz will be determined to be a matching interaction type. In certain embodiments of the presently disclosed subject matter, after receiving user input (and possibly, although not necessarily, after performing actions related to the received user input), one or more of the specified parameters may be updated dependent upon the user input (including also user's lack of input). For example, if the user participates in the interaction, e.g., selects one answer of the answers displayed in American Quiz followed by Sports content, then the parameters can be updated accordingly. Considering the specific example of user history, the conversion rate can be updated to reflect current participation with respect to American Quiz interaction type. In addition, the conversion rate of the user history parameter relating to American Quiz, when matching Sports content, can also be updated. Thus, if the conversion rate was 50% (5/10) then if the user ignored the interaction, the conversion rate drops to 45.5% (5/11), whereas if he provided an input, the conversion rate increases to 54.5% (6/11).

With respect to the example of interaction-subject history, the conversion rate of American Quiz when matching Sports content, can be updated. In a similar way, the conversion rate of the website with reference to American Quiz can be updated.

Updating one or more parameters stored in parameter data repository 290 dependent upon at least the user input, can be done by parameter updating engine 260 illustrated in Fig. 2. Arrows 413 and 414 in Fig. 4 illustrate updating the value and/or weight, respectively, of website history 440 after a decision has been reached (a score was calculated to an interaction type). Each of the values and/or weights of the other parameters 410-430 can similarly be updated after reaching a decision. Alternatively, none or only some of the parameters can be updated.

Note that the invention is not bound by the specified examples of updating conversion rates.

As previously described, after an interaction has been output through the interactive window, a user input, associated with the displayed interaction, is received through the same interactive window. User input receiver and handler 250 illustrated in Fig. 2 is configured to receive a user input associated with the interaction. Each interaction type is associated with a user input and is designated to receive a user input of a certain type, being one of a click type and a non-click type. The user input received through the interactive window is of one of the click/ non-click types.

After receiving the user input, one or more actions related to the received user input are performed. Some examples of non-advertising related actions, such as providing the user with additional interactive activity, have been detailed above.

According to certain embodiments of the presently disclosed subject matter, in response to receiving user input, an advertisement can be provided to the user. The advertisement can be selected based on the user input. Such an action can be referred to as an advertisement related action.

It should be noted that the invention is not bound by the sequence of operations performed during parameter valuation of few exemplary parameters, nor by the functionalities and structure of each of the various units referred to in Fig. 4.

Fig. 5 is a flow diagram showing an example of a sequence of operations performed during advertisement matching, in accordance with the presently disclosed subject matter.

As illustrated in Fig. 5, advertisement providing unit 510 is operatively connected to input receiver and handler 250 and advertisement data repository 520 which stores one or more advertisements.

As discussed with respect to Fig. 2, input receiver and handler 250 is configured to receive the user input fed through the interactive window and to handle it by normalizing the different formats of the input to one or more label based formations.

Each of the interaction types is designated to receive an input in a certain format. The formats of inputs can be, for example, free text, drag & drop, and selection of one answer between several options presented. The input can be normalized to one or more label based formations.

Labels represent pieces of information of different levels and kinds. For example, labels can refer to subjects (topics), in a general level such as News, Economics, Culture, Sports, or may have a more focused level, relating to a certain group included in the general level, such as Ski, Hockey, Football (included in the general level of Sports). The label can be even more focused and refer to a certain entity in the group, such as a name of a specific player. Other kinds of labels may include stative verbs such as 'love', 'hate', 'want', 'smell', etc. Labels may be a combination of different kinds of labels, for example 'love Olympic sport'. One of ordinary skill in the art would appreciate also additional kinds of labels. Note that the invention is not bound by these examples.

In certain embodiments, input receiver and handler 250 is configured to receive user input and to normalize it into label based formation, i.e., to normalize the different formats of inputs (free text, selection, etc.) into one or more labels. Each of the formats of input can be normalized using different tools. For example, in order to normalize free text known tools, such as semantic scanners used to scan content in the website to identify a contextual subject, other free text readers and analyzers can be used to extract one or more labels of the input. For example, if the following Open Question was displayed to the user: "Which Liverpool player do you admire the most?" and the user responded that he dislikes football and prefers basketball, then free text readers and analyzers can extract the following labels: 'dislike football', 'prefer basketball', 'dislike, 'prefer', 'football', and 'basketball'.

If, for example, a Poll, or American Quiz interaction types are displayed, then the selected answer of the user can be compared to predefined answers of the interaction, and labels associated with the predefined answers may be extracted. For example, if the user has been asked whether he prefers football or basketball, and he has chosen basketball, then labels associated with basketball, such as 'prefer basketball', 'prefer' and 'basketball' can be associated with the input.

The above are merely two examples of normalizing user input tools. However, other known per se techniques can also be used to normalize user input according to its format.

As exemplified above, in response to normalizing the user input, labels can be created. Alternatively or additionally, labels can be predefined and used upon normalizing user input. After input receiver and handler 250 receives user input fed through the interactive window and normalizes the user input into one or more labels, advertisement providing unit 510 is configured to receive the labels from input receiver and handler 250 and to match one or more advertisements from among one or more advertisements stored in advertisement data repository 520, based on the labels extracted from the user input. Further details of advertisement matching are illustrated below with respect to Fig. 6.

Advertisement injector 530 is configured to receive the one or more matched advertisements and to transmit, for outputting ,the one or more advertisements in web page A 106. The advertisement can be output in interactive window 280 included in web page A 106. Alternatively, the advertisement can be transmitted for outputting in another window designated for outputting advertisements.

It should be noted that the invention is not bound by the sequence of operations performed during advertisement matching, nor by the functionalities and structure of each of the various units referred to in Fig. 5.

Fig. 6 illustrates a flow diagram showing an example of a sequence of operations performed during input normalization, in accordance with the presently disclosed subject matter.

As described above, input receiver and handler 250 are configured to receive user input fed through an interactive window and to normalize it into labels. Fig. 6 illustrates three examples of user interactions: Open Question 611, Poll 612 and American Quiz 613. The inputs of interactions 611-613 are normalized into one or more labels, using different normalizing tools.

As illustrated in Fig. 6, the user input to Open Question 611, which is in the form of free text, can be normalized by free text reader and analyzer 611'. The user inputs to Poll 612 and American Quiz 613 are normalized by predefined answer tools, 612' and 613', respectively. 612' and 613' compare the user input to predefined answers. The outputs of 611', 612' and 613', once normalized, are all fed into input receiver and handler 250. The labels are used to aggregate information regarding the user, with respect to a certain subject.

User profiling 630 is configured to receive labels from input receiver and handler 250 and extract labels relating to the user profile, i.e., labels relating to user characteristics and/or preferences. For example, with reference to the above labels: 'hate football', 'prefer basketball', 'hate', 'football', 'prefer' 'basketball', user profiling 630 extracts the following labels: 'prefer basketball', 'hate football'. User profiling 630 can extract fewer or additional labels such as labels indicating characterizing details of the user, such as age, gender, status and the like.

Content profiling 640 is configured to extract labels relating to a certain subject. For example, content profiling extracts the following labels of the above example: 'basketball' and 'football'. The information aggregated by content profiling 640 is related to input received from all users with respect to different interactions displayed to them. The information can be used by an advertisement provider to better match an advertisement to a user. For example, if, according to content profiling, most users prefer basketball over football, then advertisements relating to basketball will better match the users.

In certain embodiments, advertisement providing unit 510 is configured to receive labels from user profiling 630 and content profiling 640 and match an advertisement among one or more advertisements stored in advertisement database 520.

Each of the advertisements stored in advertisement database 520 can be associated with one or more advertisement-labels. The associated advertisement-labels are indicative of the characteristics of the advertisement and can be predefined by the advertisement provider. For example, an advertisement for sportswear can be associated with labels such as 'sport' and 'adults'.

After receipt of labels from either or both user profiling 630 and content profiling 640, advertisement providing unit 510 is configured to match received labels to the advertisement-labels of one or more advertisements and select one or more advertisements having labels which best reflect a match with the received labels of profiling 630 and content profiling 640. According to one example, advertisement providing unit 510 selects the advertisement that shares the largest number of identical labels with the received labels. Yet, according to another example, advertisement providing unit 510 selects the advertisement that shares the largest number of labels having similar meaning with the received labels. Other selecting methods are also possible.

After one or more advertisements have been selected, advertisement injector 530, operatively connected to advertisement providing unit 510, is configured to receive the advertisement and to transmit for outputting the advertisement in web page A 106.

In certain embodiments of the presently disclosed subject matter, advertisement providing unit 510 is configured to match an advertising concept in terms of compensation methods to the user, prior to matching of an advertisement.

Several known compensation methods include: CPM (Cost Per Mille), CPC (Cost Per Click), CPL (Cost Per Lead) and CPE (cost per everything). Additionally or alternatively, other examples of compensation methods can also be used.

Advertisement providing unit 510 can select an advertising concept, for example, based on a user profile which stores the user's preferences with respect to advertisement concept, or based on user history 430 previously described with reference to Fig. 4, and match one or more advertisements that meet the preferred advertisement concept. With respect to the example above, the advertisement for sportswear can, in addition to labels of 'sport' and 'adults', also be associated with a label of 'CPE'. This label will be compared to information extracted from a user profile or the user history. However, it should be noted that other possible matching methods of an advertisement, of a particular concept, are possible.

It should be noted that the invention is not bound by the sequence of operations performed during input normalization, nor by the functionalities and structure of each of the various units referred to in Fig. 6.

It will also be understood that the system according to the invention may be a suitably programmed computer. Likewise, the invention contemplates a computer program being readable by a computer for executing the method of the invention. The invention further contemplates a machine-readable memory tangibly embodying a program of instructions executable by the machine for executing the method of the invention.

Claims

CLAIMS:

1) A computer-implemented method of providing a user interaction, comprising:

(ii) providing content of a web page;

(iii) providing an interactive window for integrating in said web page which facilitates outputting of at least one of said interactions and facilitates inputting of a respective user input, of said user inputs, associated therewith, wherein at least one of said received user inputs being of said non click type;

(iv) scanning said content and identifying at least one contextual subject associated with said content;

(v) determining at least one user interaction type from among said user interaction types that matches said at least one contextual subject according to a subject-interaction matching criterion(a);

(vi) transmitting for outputting through said interactive window at least one user interaction formatted based on said user interaction type that matches said at least one contextual subject; at least one of said determined user interactions type is associated with a user input of said non-click type;

(vii) receiving user input associated with said interaction and being of said non-click type; said input was fed through said interactive window; and

(viii) performing at least one action related to said received user input.

2) The computer-implemented method of claim 1 wherein said stage of (vi) further comprising outputting through said determined interactive window at least one user interaction formatted based on said user interaction type that matches said at least one contextual subject; at least one of said determined user interactions type is associated with a user input of said click type. 3) The computer-implemented method of claim 1, wherein said subject-interaction matching criterion(a) includes at least one of: interaction-subject history matching degree.

4) The computer-implemented method of claim 3, wherein said subject-interaction matching criterion(a) further includes at least one of: user history matching degree, interaction history matching degree, and website history matching degree.

5) The computer-implemented method of claim 1, wherein said action is a non- advertising related action.

6) The computer-implemented method of claim 4, wherein said non-advertising related action, includes providing the user with a second interaction related to said received user input.

7) The computer-implemented method of claim 1, wherein said action is an advertising related action.

8) The computer-implemented method of claim 7, wherein said stage (i) further includes providing a repository that includes one or more advertisements, wherein each of said one or more advertisements is associated with one or more advertisement-labels, and wherein said advertising related action includes:

(ix) normalizing said user input into one or more labels;

(x) selecting one or more advertisements from among said one or more advertisements that reflect a match between said labels and said advertisement-labels associated with said one or more advertisements; and

(xi) outputting said one or more selected advertisements in said web page.

9) The computer-implemented method of claim 1, wherein said stage (viii) further comprises:

updating said subject-interaction matching criterion(a) dependent upon at least said user input. 10) The computer-implemented method of claim 9, wherein updating said subject- interaction matching criterion(a) includes updating at least one of: interaction- subject history value and interaction-subject history weight .

11) The computer-implemented method of claim 4, wherein updating said subject- interaction matching criterion(a) includes updating at least one of: user history value, user history weight, interaction history value, interaction history weight, website history value, and website history weight.

12) The computer-implemented method of claim 1, wherein said providing in said web page of (iii) includes: integrating in a predefined area in said web page said interactive window.

13) The computer-implemented method of claim 1, wherein said user interaction is selected from a group comprising: a Poll, American Quiz, Open Question, Crossword Puzzle, an Arrow Crossword Puzzle, Anagram and Hangman.

14) The computer-implemented method of claim 3, wherein said matching degree is determined based on a conversion rate function.

15) The computer-implemented method of claim 4, wherein said matching degree is determined based on a conversion rate function.

16) A computer-implemented program storage device readable by machine, tangibly embodying a program of instructions executable by the machine to perform a method of providing a user interaction, comprising:

(ii) providing content of a web page;

(viii) performing at least one action related to said received user input.

17) A computerized device comprising at least one processing unit comprising computer memory operatively connected to at least one processing unit; the at least one processing unit is configured to:

(i) scan content of a web page and identify at least one contextual subject associated with said content;

(ii) determine at least one user interaction type that matches said at least one contextual subject according to a subject-interaction matching criterion(a); wherein said determining of at least one user interaction type is from among a plurality of user interaction types associated with one or more user inputs; wherein each user input being of a user input type that is selected from a group that includes at least a click type and a non-click type; wherein at least one of said determined user interactions type is associated with a user input of said non-click type;

(iii) transmit for outputting through an interactive window for integrating in said web page at least one user interaction formatted based on said determined user interaction type; wherein said interactive window facilitates outputting said at least one of said interactions and facilitates inputting of a respective user input, of said user inputs, associated therewith, wherein at least one of said received user inputs being of said non click type;

(iv) receive user input associated with said interaction and being of said non- click type; said input was fed through said interactive window; and

(v) perform at least one action related to said received user input.

18) The device according to claim 17 wherein said subject-interaction matching criterion(a) includes at least one of: interaction-subject history matching degree.

19) The device according to claim 17 wherein the at least one computer processor is further configured to:

(vi) normalize said user input into one or more labels;

(vii) select one or more advertisements from among one or more advertisements, wherein each of said one or more advertisements is associated with one or more advertisement-labels, wherein selecting is of one or more advertisements that reflect a match between said labels and said advertisement-labels associated with said one or more advertisements; and

(viii) output said one or more selected advertisements in said web page.

20) The device according to claim 17 wherein the at least one computer processor is further configured to:

update said subject-interaction matching criterion(a) dependent upon at least said user input.