EP2087463A1 - Applications pour le profilage d'utilisateurs de services de telecommunications - Google Patents
Applications pour le profilage d'utilisateurs de services de telecommunicationsInfo
- Publication number
- EP2087463A1 EP2087463A1 EP07821980A EP07821980A EP2087463A1 EP 2087463 A1 EP2087463 A1 EP 2087463A1 EP 07821980 A EP07821980 A EP 07821980A EP 07821980 A EP07821980 A EP 07821980A EP 2087463 A1 EP2087463 A1 EP 2087463A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- user
- profiling
- platform
- profile
- service
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Ceased
Links
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Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
Definitions
- the invention relates to the field of profiling users of telecommunications services.
- Profiling users allows customization of the information that is issued to them: publicity, location data, product catalog and services, for example.
- the profiling of Internet users has been the subject of many technical developments. More than one billion pages are potentially visible on the web, where personalization of information is one of the solutions that can help to keep the web as a viable information resource.
- the personalization of information is of particular importance for e-commerce. Indeed, the extremely fast development of the Internet indust a wealth of information for each type of product or service, with the possibility of buying or contracting online, so that the consumer is faced with a "hypercnolx" and is less faithful, more versatile. Switching from one website to another by a simple click is as usual and quick as zapping from one channel to another of a satellite package or browsing through a paper encyclopedia.
- One to one marketing is a response to the plethora of information on the web. The provider offers the identified surfer services, information and personalized products, which interest him a priori really.
- mobile commerce is meant here the possibility of carrying out through a mobile communication terminal financial transactions for purchases of goods and services or trading operations.
- Proficient users of 3G services is therefore also important. This is of course the case for mobile commerce, as has been said more generally about e-commerce. This is also the case of the "location" service, for the delivery of information taking into account both the location of the mobile terminal and the interests of its user.
- Document FR-2810183 illustrates such an idea; a server sends to the PDA a vectorized cartographic representation of the place where the user is, with display of the places of interest to the user, the types of places of interest to the user being known to the server.
- the profiling of a user of services includes the following steps: collecting data relating to the user; constructing the user's profii; user modeling.
- the collection of data is conventionally a data extraction in a database of users, this bank having been fed by various technical means.
- the TCP / IP protocol involves the provision of an IP address, and also allows the server to know Its following data: navigation software brand, version of this navigation software, date and time of the connection, page on which is implemented an invisible hyperlink.
- a large number of tools are used to automatically collect data relating to the user, for example cookies, PSN (Serial Number Processor), unique identification number GU ID (Global Unique Identifier), BHO (Browser Helper Objects), images GIF [web bug] or pointer (tag) html hidden in micro image in a web page.
- PSN Serial Number Processor
- GU ID Global Unique Identifier
- BHO Brownser Helper Objects
- the cookie is most commonly used for one-to-one marketing. It also allows you to customize the publicity .
- These are the browsers that physically manage cookies on behalf of Internet sites. Each cookie can store up to 4096 characters and browsers can create up to twenty cookies per site. Cookies make navigation more comfortable (integration of preferences, for example language), answers to questions already asked, automatic display of the user's name, geographical location, adapted advertising.
- Service user modeling takes into account personal information (eg age, language), preferences and interests, and the user's history of service usage.
- canonical matching a current user is cataloged against a typical predefined user.
- the model of the user is obtained by inference, from information collected implicitly when using the services.
- the behavior of the user is comparable to that of a group of users.
- statistical tools are used; linear tools, Markovian, network of neu rones, classification, rule induction, Bayesian network.
- the construction of the service user profile can be explicit, implicit or supervised.
- the information is provided directly by the user. This information can be entered by the user or automatically obtained by the system.
- the implicit construction of the user's profile is based on a method of contextualization and preferences of the user via his behavior when using the services. This implicit construction conventionally implements Bayesian classifications, neural networks, or genetic algorithms. Supervised construction asks the consumer how satisfied they are with each response generated by the service provider.
- a video can be streamed from an internet server to a PC terminal, or broadcast by cable to a television screen, or multicast in a 3G network of mobile communication terminals.
- profiling techniques currently proposed concern specific areas of application: Internet, telephony, for specific purposes.
- Goggie Analytics For the Internet, Goggie recently introduced a product called Goggie Analytics, aimed at website owners, to learn how their visitors interact with sites and to identify bottlenecks in the world. the traffic is tight ⁇ bottlenecks ⁇ , and to determine the most effective keywords in the search engines.
- document FR-2875040 describes a method and a device for analyzing navigation on a site. Markers are incorporated into the pages of the Internet site, preferably all pages.
- the document FR 2785040 designates a program whose function is to send to the site data concerning the page, the visitor, the communication session between the visitor and the site and the interactions between the visitor and the visitor. Sit down.
- This program is for example in HTML (Hyper Text Markup Language).
- the marker implements for example the technique of cookies.
- An interesting event is chosen: for example access to general sales conditions.
- a server performs a learning to learn differences between the behavior of "random" visitors who have not triggered the event, and the behavior of the "particular” visitors who triggered the event when they visited the site. the site.
- the server implements a neural network.
- a communication element is incorporated into the transmitted page. to the current visitor (eg flash banner, pop-up window).
- the server performs a self-learning of the i ncidence of the communication event on the occurrence of the event of interest. The communication elements that were most helpful in the coming of the interesting event are thus selected, For the telecommunication service platforms, the company
- Siemens offers a product called Service Delivery Manager tSM (Tango SM) for broadband services.
- Nokia Technlogy Platform has developed a software for Nokia 60 series smartphones, allowing to collate Its usage data (40 to 30 kB / month / user). From a panel of volunteer users, data mining (data mining) has identified user profiles and uses (see Hannu Verkasalo, Handset-Based Monitoring of Mobile Customer Behavior).
- the document G B236 ⁇ 699 describes means for profiling the behavior of mobile phone users, for the detection of fraud.
- the applicant's document FR2792484 describes a personalized communications network.
- a starter contains information on the users (personalities, habits) and on the terminal (characteristics of the graphic interface, the audio interface , processor working frequency ⁇ User data is pre-loaded or provided online
- a user interface is built according to the user's request, this interface containing only suitable objects or applications
- EP 1 21 1 61 8 discloses a method and a device for providing multimedia terminal advertising, regardless of the type of terminal. connected to a communication terminal, these portable means Including a processor and a memory
- the user's profile is stored in the memory.
- the processor recognizes the type of terminal and selects, in the memory, the advertisements adapted to the type of termina! recognized and in the profile of the user.
- the profiling technique according to the invention must make it possible to aggregate all the available information on the behavior of consumers of telecommunications services, as well as on their equipment,
- the invention relates, according to a first aspect, to a computer program product comprising instructions for profiling a telecommunications service user in a multi-platform environment, the product comprising: an explicit profiling function block, gathering information about the user's preferences, directly from that user;
- the product further comprises a configuration functional block, gathering the behavior characteristics of the user for a platform introduced into the environment, these characteristics being broken down between those already included in the user's profile and new ones, an extension functional block ensuring the aggregation of these new features
- the product further comprises a request functional block, providing an access and request interface for applications whose operation depends on the profile of the user.
- a confidentiality function block takes into account the legal constraints and / or the wishes of the users with regard to storing the personal data.
- the invention relates to a server comprising means for receiving a call-up request from a user terminal destined for at least one service delivery platform, said server comprising :
- implicit profiling means of the user gathering the raw data relating to the behavior of the user for each service delivery platform, these implicit profiling means comprising means for aggregating these raw data;
- the invention relates, in a third aspect, to a network comprising a server as presented above and a plurality of service delivery platforms to mobile communication terminals.
- FIG. 1 is a schematic view of a multiplatform operator environment embodying the invention, in one embodiment
- Figure 2 is a schematic view of a configuration of a multi-platform profile generator according to the invention.
- FIG. 1 schematically shows a telecommunications service delivery environment 1.
- a first platform 2 delivers videos to mobile terminals
- a second platform 3 delivers at least one television program for mobile terminals
- a third platform 4 delivers at least one Internet television program (Internet Protocol Television)
- a fourth platform 5 delivers IP communication services (e-learning, IMS IP Multimedia Subsystem).
- a program module automatically aggregates the service usage data from the different platforms 2-5. Subsequently, this program module 6 is called Profile Enabler, the term Enabier conventionally denoting a technological solution supporting a single feature.
- the Profile Enabier 6 includes several blocks for specific functions.
- the explicit profiling block 7 collects the information on the preferences of the users U directly with these users, for example via a user-friendly interface. This interface is particularly accessible via the Internet.
- the implicit profiling block 8 is in charge of collecting the basic data of the user for each service delivery platform 2-5. This implicit profiling block 8 implements the aggregation and / or the inference for the user. update the attributes of the user's profile.
- the basic data concerning the users U are, for example, the recording of service session logs.
- Some examples of raw data are given below from a video on demand (Video on Demand VoD) server. :
- a data structure describing the teacher! of the user is defined. It can include typical user information such as age, gender, mother tongue, as well as data on service consumption statistics (video, messaging). Another set of information is formed by the semantic data (centers of interest, category of consumer). Some examples of consumption and interest data are given below:
- Video #streamed videos / day / WE, #downloaded videos / day / WE, average session duraii ⁇ n ...
- the list of all the characteristics describing the profile of the user and his behavior is designated by the profile data vector (PDV).
- PDV profile data vector
- Some of the attributes of the user profile are defined as core features, while other attributes are specialized to be used based on the service delivery platforms present in a given environment.
- the modification of environment 1 by adding or deleting a platform is treated as follows in profile enabler 6.
- the block works! configuration 10 ⁇ e ⁇ abler configuration) supports the introduction of new service provisioning platforms 1 1 in the environment.
- a new service delivery platform results in the creation of new features that were not present in the profile data vector. This is the role of the extension functional block 12.
- the aggregation / inference logic is defined for these new features 13.
- a new service provider platform 1 1 may require user profile characteristics. that are already present in the profile data vector.
- the logic of aggregation / inference is adapted to take into account the new information sources for their aggregation to the existing profile.
- the confidentiality block 16 takes into account the legal constraints regarding the storage and analysis of the personal data of the users.
- the Profile Enabler 6 must provide extraction capabilities that can be used by various applications 17: targeted advertising, personalized information, network applications based on the user's experience to access aggregated data.
- the Request Profile Block 18 ⁇ Profile Data Query provides an access and query interface for applications 17 that utilize its user profile data (e.g., an API application program interface for SQL database).
- the Enabier profile can be used by two main categories of applications:
- profiling information to deliver a more dedicated and targeted service to profiled consumers: targeted advertising, graphical user interfaces depending on the type of user (experienced users and basic users), recommendation systems (in Internet browsing, recommendation of products and services in mobile commerce); - applications that use profile data inherently to their logical service: custom-content applications, or social network applications.
Abstract
Description
Claims
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
FR0654703A FR2908212B1 (fr) | 2006-11-03 | 2006-11-03 | Applications pour le profilage d'utilisateurs de services de telecommunications |
PCT/EP2007/061625 WO2008052966A1 (fr) | 2006-11-03 | 2007-10-29 | Applications pour le profilage d'utilisateurs de services de telecommunications |
Publications (1)
Publication Number | Publication Date |
---|---|
EP2087463A1 true EP2087463A1 (fr) | 2009-08-12 |
Family
ID=38036382
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
EP07821980A Ceased EP2087463A1 (fr) | 2006-11-03 | 2007-10-29 | Applications pour le profilage d'utilisateurs de services de telecommunications |
Country Status (4)
Country | Link |
---|---|
US (1) | US20100138278A1 (fr) |
EP (1) | EP2087463A1 (fr) |
FR (1) | FR2908212B1 (fr) |
WO (1) | WO2008052966A1 (fr) |
Families Citing this family (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8108329B2 (en) * | 2008-05-06 | 2012-01-31 | Richrelevance, Inc. | System and process for boosting recommendations for use in providing personalized advertisements to retail customers |
US8019642B2 (en) * | 2008-05-06 | 2011-09-13 | Richrelevance, Inc. | System and process for receiving boosting recommendations for use in providing personalized advertisements to retail customers |
US8364528B2 (en) | 2008-05-06 | 2013-01-29 | Richrelevance, Inc. | System and process for improving product recommendations for use in providing personalized advertisements to retail customers |
US8583524B2 (en) * | 2008-05-06 | 2013-11-12 | Richrelevance, Inc. | System and process for improving recommendations for use in providing personalized advertisements to retail customers |
US20100287031A1 (en) * | 2009-05-07 | 2010-11-11 | Mckenna Charles | Method, Apparatus, System, and Computer Program for Selecting Replacement User Devices |
US9009226B2 (en) * | 2009-12-09 | 2015-04-14 | Microsoft Technology Licensing, Llc | Generating activities based upon social data |
FR2977345A1 (fr) * | 2011-06-30 | 2013-01-04 | Alcatel Lucent | Systeme de recommandation de contenu numerique |
US9137651B2 (en) | 2011-11-22 | 2015-09-15 | International Business Machines Corporation | Systems and methods for determining relationships between mobile applications and electronic device users |
US20130173323A1 (en) * | 2012-01-03 | 2013-07-04 | International Business Machines Corporation | Feedback based model validation and service delivery optimization using multiple models |
CN111487563B (zh) * | 2020-05-15 | 2022-02-15 | 国网江苏省电力有限公司电力科学研究院 | 基于遗传算法及属性支持度的变压器状态知识获取方法及设备 |
Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP1557996A1 (fr) * | 2004-01-23 | 2005-07-27 | Hewlett-Packard Development Company, L.P. | Service de profil d'utilisateur |
Family Cites Families (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7242988B1 (en) * | 1991-12-23 | 2007-07-10 | Linda Irene Hoffberg | Adaptive pattern recognition based controller apparatus and method and human-factored interface therefore |
EP1095518A1 (fr) * | 1998-07-02 | 2001-05-02 | MCALLAN, Robert E. | Acces a l'information avec capacite de commercialisation selective |
AU5465099A (en) * | 1998-08-04 | 2000-02-28 | Rulespace, Inc. | Method and system for deriving computer users' personal interests |
US20040054572A1 (en) * | 2000-07-27 | 2004-03-18 | Alison Oldale | Collaborative filtering |
JP4552296B2 (ja) * | 2000-09-08 | 2010-09-29 | ソニー株式会社 | 情報処理装置および情報処理方法、並びに記録媒体 |
US20060195583A1 (en) * | 2003-02-27 | 2006-08-31 | Fabio Bellifemine | Method and system for providing information services to a client using a user profile |
US7590705B2 (en) * | 2004-02-23 | 2009-09-15 | Microsoft Corporation | Profile and consent accrual |
US20070150368A1 (en) * | 2005-09-06 | 2007-06-28 | Samir Arora | On-line personalized content and merchandising environment |
US20070266031A1 (en) * | 2006-05-15 | 2007-11-15 | Adams J Trent | Identifying content |
-
2006
- 2006-11-03 FR FR0654703A patent/FR2908212B1/fr not_active Expired - Fee Related
-
2007
- 2007-10-29 EP EP07821980A patent/EP2087463A1/fr not_active Ceased
- 2007-10-29 WO PCT/EP2007/061625 patent/WO2008052966A1/fr active Application Filing
- 2007-10-29 US US12/447,593 patent/US20100138278A1/en not_active Abandoned
Patent Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP1557996A1 (fr) * | 2004-01-23 | 2005-07-27 | Hewlett-Packard Development Company, L.P. | Service de profil d'utilisateur |
Also Published As
Publication number | Publication date |
---|---|
WO2008052966A1 (fr) | 2008-05-08 |
US20100138278A1 (en) | 2010-06-03 |
FR2908212A1 (fr) | 2008-05-09 |
FR2908212B1 (fr) | 2008-12-26 |
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