US20110106528A1

US20110106528A1 - Method and System to Automatically Change or Update the Configuration or Setting of a Communication System

Info

Publication number: US20110106528A1
Application number: US12/913,176
Authority: US
Inventors: Paul Maddison
Original assignee: Siemens Enterprise Communications GmbH and Co KG
Current assignee: RingCentral Inc
Priority date: 2009-10-29
Filing date: 2010-10-27
Publication date: 2011-05-05
Also published as: EP2317730B1; US10303774B2; JP2014038632A; JP5762489B2; US10650194B2; CN102055793A; CN102055793B; KR20170008317A; KR20130111509A; EP2317730A1; KR20150010003A; US20150213005A1; JP2011096259A; KR102009912B1; US20190243901A1

Abstract

A method and device for automatically changing or updating a configuration or setting of a communication system is disclosed. In one aspect, the method includes providing information to the communication system, the information comprising natural human language, storing the information in a digital storage device, detecting a triggering event in the information, and changing the configuration or setting of the communication system automatically using a processor. The information is an input to the communication system, an input from at least one alternate communication system, or a combination of an input to the communication system and an input from the at least one alternate communication system.

Description

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims foreign priority from European application No, EP09013603.7 filed on Oct. 29, 2009 and European application No. EP10004021.1, filed on Apr. 15, 2010. This application incorporates by reference both of those applications herein in their entirety.

FIELD OF INVENTION

The present invention relates generally to a method and a system to automatically change or update the configuration or setting of a communication system.

BACKGROUND OF THE INVENTION

Different systems and methods are well-known in the art, providing various kinds of communication services. Examples of such systems are phone switching systems, instant messaging systems and so-called social media network systems, like e.g. Twitter, LinkedIn or Facebook. Among these, public, office, or private systems may be distinguished. All of these systems provide their special set of services based on their special representation of the end-user and its respective data base. The results are disjoint communications streams, characterized by a certain degree of user-unfriendliness due to e.g. multiple presence status fields to look after and to be manually maintained. Furthermore, if done very frequently during the day, starting calls and conferences manually may be experienced as a hassle by the user.
The goal of facilitating the use of such modern communication systems has been approached in the art by distributing numerous synchronization applications (“Sync Apps”) to bridge information between different systems. As an example, the application “TwitterApp” for the Facebook service allows the Facebook status to be synchronized up with the Twitter status of user. Unfortunately, these kind of applications are restricted to merely translating a status information from one data base to the respective entry in the data base of another communication service. To further facilitate call set up, there are so-called click-to-call or click-to-conference applications available which however reside in only one of the many used communication systems.

SUMMARY OF THE INVENTION

The present invention aims at improving the facility of use of modern communication systems by providing a method and a device to automatically change or update the configuration or setting of a first communication system, the method using information gathered by the first communication system or information provided by a second communication system or both kinds of information. According to the invention, the used information comprises natural human language.
According to one embodiment of the present invention a method is disclosed for automatically changing or updating a configuration or setting of a communication system comprising providing information to the communication system, the information comprising natural human language, storing the information in a digital storage device, detecting a triggering event in the information, and changing the configuration or setting of the communication system automatically using a processor. The information is an input to the communication system, an input from at least one alternate communication system, or a combination of an input to the communication system and an input from the at least one alternate communication system.
In another embodiment of the present invention a device is disclosed for automatically changing or updating a configuration or setting of a communication system comprising a processor providing information to the communication system, the information comprising natural human language. The information is an input to the communication system, an input from at least one alternate communication system, or a combination of an input to the communication system and an input from the at least one alternate communication system. The device further includes a digital storage device storing the information, the processor detecting a triggering event in the information, and the processor automatically changing the configuration or setting of the communication system.
In the context of the present disclosure, the term of automatically changing or updating a configuration or a setting of a communication system covers all kinds of such changes or update processes, which are at least assisted, in many cases carried out completely by an information processing system, which preferably couples different disjoint communication systems together through intelligent and user-friendly means, preferably employing some kind of context sensitive trigger mechanism. This process of automatically changing or updating the configuration or setting of a communication system may be performed by using information gathered by the communication system to be changed or updated or by using information provided by another communication system or by employing both kinds of information in various kinds of combination.
The use information for changing or updating the configuration of setting of a communication system comprises natural human language of any kind or in any form, e.g. human speech recorded by sampling and converting acoustic signals to the digital domain or natural human language in the form of symbol sequences as e.g. text files, e-mails, short message services or parts of such information entities. Different kinds of natural human language, such as digital speech and text messages or parts thereof may be combined. According to one preferred embodiment of the present invention, the first communication system gathers information by collecting status information or status change information from at least one server used by at least one second communication system. For example, the communication system Facebook has a feature called “status updates” (also referred to simply as “status”) which allows users to post messages for all their friends to read. In turn, friends can respond with their own comments, and also press the “Like” button to show that they enjoyed reading it. A user's most recent status update appears at the top of their profile, and is also noted in the “Recently updated” section of a user's friend list.
Originally, the purpose of the feature was to allow users to inform their friends of their current “status” (i.e. their current feelings, whereabouts or actions) by referring to themselves in the third person (e.g. “George is happy” or “John is with Robert at his house”). However, users are no longer required to write in the third person.
Facebook originally prompted the status update with “User name is . . . ” and Facebook users filled in the rest. Later on, the requirement to start a status update with “is” was removed. The question “What are you doing right now?” was introduced. In March 2009, the status update question was changed from “What are you doing right now?” to “What's on your mind?”
Later on, Facebook added the feature to tag certain friends (or groups etc) within one's status update by adding an @ character before their name, turning the friend's name into a link to their profile and including the message on the friend's wall. In 2009, the communication system Myspace also added a new status update feature. If a Myspace user has a Twitter account, the tweet will also update the Myspace status. Other leading social networking websites Facebook, MySpace, LinkedIn, and XING also have their own status update feature, also known as microblogging.
With the increasing use of microblogging, many users want to maintain presence in more than one social network. Services such as Lifestream and Profilactic will aggregate microblogs from multiple social networks into a single list. Services such as Ping.fm will send out your microblog to multiple social networks. Facebook has a similar feature. It does, however, require that the two accounts to be synchronized (“synched up together”) by a corresponding synchronization action of a user or administrator.
According to the present invention, the use information for changing or updating the configuration of setting of a communication system comprises natural human language of any kind or in any form, e.g. human speech recorded by sampling and converting acoustic signals to the digital domain or natural human language in the form of symbol sequences as e.g. text files, e-mails, short message services or parts of such information entities. Different kinds of natural human language, such as digital speech and text messages or parts thereof may be combined.
According to another preferred embodiment of the present invention which may be combined with other embodiments of this invention, the first communication system gathers information by employing at least one keystroke listener running on at least one terminal device used by user of the first communication system.
According to another preferred embodiment, which may be combined with other embodiments of this invention, an expression matching step is performed with used natural human language data. In this way, expressions or groups of such expressions may be detected in used natural human language data and may be used to control subsequent actions which have been associated with such expressions.
According to another preferred embodiment which may be combined with other embodiments of the present invention, a step of extracting change or update information from the used natural human language data and a step of changing or updating the configuration or setting of the first communication system according to the extracted change or update information is performed during the method according to the present invention. In this way, expressions detected in the matching step or other expressions that may be associated with subsequent actions, such as change or update information may be extracted from the used natural human language data, and the configuration or setting of the first communication system may be changed or updated according to the extracted change or update information.
According to a further preferred embodiment of the present invention which may be combined with other embodiments of the invention, at least one communication action is performed by the first communication system, the action being triggered by a change or update of the configuration or setting of the first communication system according to information comprising natural human language used by the first communication system.
According to another preferred embodiment which may be combined with other embodiments of the invention, a learning algorithm based on a monitoring of correlated behavior of at least one user of at least one first or second communication system will be used as part of a method according to the present invention. The person skilled in the art knows various kinds of learning algorithms which may be used in this context. Examples of such learning algorithms may be so-called rule based learning algorithms or other kinds of adaptive algorithms which are suitable to adapt to correlations in the behavior of at least one user of at least one first or second communication system that may be observed by monitoring of such behavior.
According to another preferred embodiment which may be combined with other embodiments of a present invention, the learning algorithm comprises a discrete optimization algorithm, aiming at optimizing an objective function that represents at least certain aspects of the user-friendliness of at least one first or second communication system.
According to another preferred embodiment of the present invention which may be combined with other preferred embodiments, the discrete optimization algorithm is a stochastic optimization algorithm. Stochastic optimization (SO) methods are optimization algorithms which incorporate probabilistic (random) elements, either in the problem data (the objective function, the constraints, etc.), or in the algorithm itself (through random parameter values, random choices, etc.), or in both. The concept contrasts with the deterministic optimization methods, where the values of the objective function are assumed to be exact, and the computation is completely determined by the values sampled so far.
Partly-random input data arise in such areas as real-time estimation and control, simulation-based optimization where Monte Carlo simulations are run as estimates of an actual system, and problems where there is experimental (random) error in the measurements of the criterion. In such cases, knowledge that the function values are contaminated by random “noise” leads naturally to algorithms that use statistical inference tools to estimate the “true” values of the function and/or make statistically optimal or near optimal decisions about the next steps. Methods of this class include stochastic approximation, stochastic gradient descent, etc.
On the other hand, even when the data is exact, it is sometimes beneficial to deliberately introduce randomness into the search process as a means of speeding convergence and making the algorithm less sensitive to modeling errors. Further, the injected randomness may provide the necessary impetus to move away from a local solution when searching for a global optimum. Stochastic optimization methods of this kind include simulated annealing, stochastic hill climbing, evolutionary algorithms, genetic algorithms etc.
A genetic algorithm (GA) is a search technique increasingly used in computing to find exact (optimal) or approximate (near optimal) solutions to optimization and search problems. Genetic algorithms may be categorized as global search heuristics. Genetic algorithms may be regarded as a special subgroup of evolutionary algorithms (EA) that use techniques inspired by evolutionary biology such as inheritance, mutation, selection, and crossover. Genetic algorithms may be implemented in a computer simulation, in which a population of abstract representations (sometimes referred to as “chromosomes” or the “genotype of the genome”) of candidate solutions (called “individuals”, “creatures”, or “phenotypes”) to an optimization problem evolves toward “better” solutions.
Frequently solutions are represented in binary form as strings of 0's and 1's, but other encodings are also possible and commonly used. The evolution usually starts from a population of randomly generated individuals and usually happens in generations. In each generation, the “fitness” of every individual in the population is evaluated, multiple individuals are stochastically selected from the current population (based on their fitness), and modified (recombined and possibly randomly mutated) to form a new population. The new population is then used in the next iteration of the algorithm. Commonly, the algorithm terminates when either a maximum number of generations has been produced, or a satisfactory fitness level has been reached for the population. If the algorithm has terminated due to a maximum number of generations, a satisfactory solution may or may not have been reached.
According to another aspect of the present invention, a system, arrangement, apparatus or device performing a method or employed by a method according to one of the disclosed embodiments of the invention is provided.
According to a preferred embodiment, the invention is providing a context sensitive trigger mechanism, which couples different disjoint communication systems together through intelligent and user friendly means, especially by that of natural human language. The invention may be further illustrated by an example based on two well-known communication systems, namely Twitter and OpenScape.
In one example, in a Twitter post (“Tweet”) a user types “I am out for lunch now”, the action by the context sensitive trigger mechanism is then to change the OpenScape one number service to voice mail, e.g. to transfer the phone of the user automatically to his voice mail without requiring any further interaction by the user.
In another example, in a Tweet reply to several people, a user may post “We really need to have conference calls on this issue”. In this case the action by the context sensitive trigger mechanism will be to set up automatically a voice conference in the OpenScape system including all people in the reply. The user now just needs to click on “start” to initiate the conference. If the user had typed “ . . . need to have a conference now” or “ . . . a conference at 2 pm” the context sensitive trigger mechanism would trigger the OpenScape system to initiate the conference call immediately without any further user interaction or send out an e-mail invitation for 2 pm.
In another example, a Tweet like, e.g. “I just landed in Boston” triggers the context sensitive trigger mechanism to activate the specific role profile in OpenScape which in this case would adapt the time of day routing rules to follow the right time zone.
A context sensitive trigger mechanism in the sense of the disclosure of the present invention may preferably use the following components:
A first useful component is the collection of the existing status change information from the servers used by the communication systems.
Through the application's programming interfaces (APIs) offered by most communication systems, namely e.g. the Twitter REST-full APIs or the Facebook APIs or “MySpace” APIs or any other blog status API, the context sensitive trigger mechanism calls or is notified about any activity or posting on the respective communication system. This listening process or service can run locally on the user's personal computer (PC) or centrally on a server, e.g. the OpenScape server.
An alternative but also preferred method to collect the desired information is to use a keystroke listener installed on the user's PC. This introduces the advantage of capturing all of the information inputted by the user, including information outside the communication systems. On the other hand it does not capture the information posted without the computer, e.g. a Tweet posted through an SMS from a mobile phone. Therefore, a combination of both methods may be preferable in some situations to capture both kinds of information.
A further useful component is some kind of e.g. iterative expression matching of certain key words inside the collected information.
The collected information, preferably collected as described before, is preferably continuously scanned through an expression matching algorithm, preferably in the following way: There may be a top level matching to look for the main content according to some key words, e.g. “conference”, “call”, “out”, “lunch”, etc. Then a context specific matching may be applied dependent on the found top level match, e.g. in the case of “conference” more specific information such as the time or the persons to be involved in the conference may be determined.
A further useful component is some kind of mapping and triggering of determined action to the communication representation of the user in the other communication system.
The desired actions, like the automated setting up of a conference is then preferably triggered by a context sensitive trigger mechanism by for example

- mapping the user data from the communication systems, which provided the information gathered, preferably according to the above disclosure, to the user representation in the user data base of the target communication system, where the desired action is to be performed and
- triggering the action through the interfaces provided by the target communication system.

A preferred embodiment of the invention may include the extension of communication user data base with the social network needed to be done up front (at setup of user). Other preferred embodiments of the invention may include a meta user data base service.
The keywords on top level or on the following context sensitive search level which have to be considered may be configured by an administrator. Such a configuration of the context trigger rules can be done in several ways.

- Predefined match lists may be included in the context sensitive trigger mechanism by default, e.g. pre-programmed by the developers of the context sensitive trigger mechanism.
- A user may have the option of self-configuration. In this case, the user can add, change or remove trigger rules.
- A self-learning context sensitive trigger mechanism can detect automatically statistical correlations in the user's communication behavior, and based on that information suggest or create autonomously new trigger rules, e.g. in the case of Twitter and OpenScape UC the following scenario can be applied: A user, who regularly—after setting Twitter to follow person X—also adds the same person in his UC contact list, would be presented by the context sensitive trigger mechanism were the option to have a new context sensitive trigger rule stating that any Twitter follower setting action, automatically triggers the addition to the UC contact list.

In order to map the two different accounts and user data base entries of the same physical user in the involved communications systems, the context sensitive trigger mechanism needs to bridge these so far disjointed pieces of information. It needs to perform the federation of the user data between different communication systems. The context sensitive trigger mechanism therefore preferably uses the e-mail-address as common and unique identifier and scans regularly the respective data bases through their provided APIs.
Among the advantages of the invention disclosed so far, the following points deserve special attention. The invention facilitates to automate the creation of communication actions using triggers in natural language instead of machine commands or triggers from status information from advanced internet (web 2.0) services or social networking services, or triggers from personal Twitter posts or similar communication services.
Preferably, the context sensitive trigger mechanism not only transfers one piece of information from one communication system to another but interprets that information first based on some intelligence and then triggers the right associated behavior on the other communication system.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 shows a first communication system;

FIG. 2 shows a change or update of the configuration or setting of a first communication system according to some preferred embodiments of the present invention;

FIG. 3 shows a change or update of the configuration or setting of a first and a second communication system according to some preferred embodiments of the present invention.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

As illustrated by FIG. 1, a user 20 inputs information 4, 5 into a first communication system 1 or receives such information from this communication system. The information input or the information received by the user 20 may comprise all kinds of information, including but not limited to texts 5 or other digital information 4, like e.g. speech data, digital images, etc. The information may be provided through a user interface 11 shown in FIG. 2, wherein the user interface may include a microphone, a keyboard, or other communication input system. The information 6 input into or received from the first communication system 1 will in general be stored in a digital storage device 2. Also stored in some digital storage device 2 of the first communication system 1 will in general be some kind of configuration or setting information in the form of some kind of information records 3, including status information and other user specific information.
The automatic change or update of the configuration 3, or setting of the first communication system 1, uses e.g. information 9 gathered by the first communication system, as shown in FIGS. 1 and 2 or information 12 provided by a second communication system 1′, as shown in FIG. 3, or both kinds of information, and the used information comprises natural human language. The automatic change or update is done by some information processing means 7, e.g. a processor of one of the communication systems involved or a processor in a user device connected to one of the communication systems involved. The information processing means 7 analyses the natural human language information, preferably by employing an expression matching step performed with used natural human language data and preferably by extracting change or update information from the used natural human language data.
Upon detection of a triggering event in the communication streams 9, 12, a context sensitive trigger mechanism may preferably trigger 10, 10′ an update of the configuration 3, 3′ or setting by suitably changing the contents of the corresponding information records in at least one of the storage devices 2, 2′ of at least one of the communication systems 1, 1′ involved.
The invention has been described in preferred embodiments and complemented with supporting figures, but is not limited thereto. Those skilled in the art will recognize that a number of additional modifications and improvements can be made to the invention without departure from the essential spirit and scope. The scope of the invention should only be limited by the appended set of claims.

Claims

1. A method for automatically changing or updating a configuration or setting of a communication system comprising:

providing information to the communication system, the information comprising natural human language;

storing the information in a digital storage device;

detecting a triggering event in the information; and

changing the configuration or setting of the communication system automatically using a processor; and

wherein the information is an input to the communication system, an input from at least one alternate communication system, or a combination of an input to the communication system and an input from the at least one alternate communication system.

2. The method of claim 1, further comprising gathering the information by collecting status information from at least one server used by the communication system.

3. The method of claim 1, further comprising the communication system gathering information by employing at least one keystroke listener running on at least one terminal device used by the communication system.

4. The method of claim 1, further comprising matching an expression contained in the information with natural human language data and extracting matched human language information.

5. The method of claim 4, further comprising changing the configuration or setting of the communication system according to the matched human language information.

6. The method of claim 5, further comprising the communication system performing at least one communication action, the communication action being triggered by a change of the configuration or setting of the communication system according to the matched human language information.

7. The method of claim 1, wherein the processor comprises a learning algorithm based on a monitoring of correlated behavior of at least one user of the communication system.

8. The method of claim 7, wherein the learning algorithm is a discrete optimization algorithm.

9. The method of claim 7, wherein the learning algorithm is a stochastic optimization algorithm.

10. The method of claim 1, wherein the processor is a processor of the communication system, a processor of the at least one alternate communication system, a processor in a user device connected to the communication system, or a processor in a user device connected to the at least one alternate communication system.

11. A device for automatically changing or updating a configuration or setting of a communication system comprising:

a processor that provides information to the communication system, the information comprising natural human language;

a digital storage device that stores the information;

the processor that detects a triggering event in the information; and

the processor that automatically changes the configuration or setting of the communication system; and

12. The device of claim 11, wherein the processor gathers the information by collecting status information from at least one server used by the communication system.

13. The device of claim 11, wherein the processor gathers information by employing at least one keystroke listener running on at least one terminal device used by the communication system.

14. The device of claim 11, wherein the processor matches an expression contained in the information with natural human language data and extracts matched human language information.

15. The device of claim 14, wherein the information processing means changes the configuration or setting of the communication system according to the matched human language information.

16. The device of claim 15, wherein the communication system performs at least one communication action, the communication action being triggered by a change of the configuration or setting of the communication system according to the matched human language information.

17. The device of claim 11, wherein the processor has a learning algorithm based on a monitoring of correlated behavior of at least one user of the communication system.

18. The device of claim 17, wherein the learning algorithm is a discrete optimization algorithm.

19. The device of claim 18, wherein the learning algorithm is a stochastic optimization algorithm.

20. The device of claim 11, wherein the processor is a processor of the communication system, a processor of the at least one alternate communication system, a processor in a user device connected to the communication system, or a processor in a user device connected to the at least one alternate communication system.