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WO2002008991A1 - Adaptation de l'information au comportement ou aux préférence d'un utilisateur par optimisation automatique - Google Patents

Adaptation de l'information au comportement ou aux préférence d'un utilisateur par optimisation automatique Download PDF

Info

Publication number
WO2002008991A1
WO2002008991A1 PCT/SE2001/001636 SE0101636W WO0208991A1 WO 2002008991 A1 WO2002008991 A1 WO 2002008991A1 SE 0101636 W SE0101636 W SE 0101636W WO 0208991 A1 WO0208991 A1 WO 0208991A1
Authority
WO
WIPO (PCT)
Prior art keywords
user
information
behaviour
assigned
group affiliation
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
Application number
PCT/SE2001/001636
Other languages
English (en)
Inventor
Erik Wallin
Erik Herou
Mikael Uvebrandt
Filip Asp
Henrik Dyberg
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
ADAPTLOGIC AB
Original Assignee
ADAPTLOGIC AB
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by ADAPTLOGIC AB filed Critical ADAPTLOGIC AB
Priority to AU2001271217A priority Critical patent/AU2001271217A1/en
Publication of WO2002008991A1 publication Critical patent/WO2002008991A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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

Definitions

  • the present invention relates to a method and a system for assigning a user a group affiliation and refining the group affiliation in accordance with the behaviour of the user.
  • the invention divides users into groups and supplies a specific presentation of information to each group.
  • the invention is intended primarily for use in server environments for information available on the Internet.
  • the information is typically transmitted from a supplier of information and services to the client system of an end user for receipt of information, but the system is not limited to this model.
  • server system can in some way adapt the information presented so that what is expected to be of most interest to the user is seen first and most clearly, the likelihood increases of the user finding the information service useful and making use of it in such a manner that the goal of the information supplier is fulfilled.
  • Patent publications WO 98/02835, WO 99/16003, US-A-5 862 325 and US-A-5 956 693 describe such a system but they are unable to divide the users into several different groups to optimize group affiliation in a controlled and automatic manner.
  • the systems permit various users to be assigned different user categories either by a system administrator or manually by the users themselves. Manual assignment is achiev- ed by the user expressly choosing various area of interest or objects related to various areas of interest.
  • System-administrative assignment occurs either by a system operator selecting manually which users shall belong to a group or by the system itself choosing affiliation by means of various statistical methods.
  • the point of departure of the invention is a system and a method for adapting information to a user's behaviour or preferences.
  • the adaptation takes place with automatic optimisation by said user being identified and assigned a group affiliation, in that information is selected based on said group affiliation, in that said user's behaviour is registered, in that said user's behaviour and/or history is analysed, and in that the result of said analysis and other available information is utilised to refine the next information selection for said user.
  • Group affiliation may be assigned to the user permanently or temporarily.
  • the group affiliation division is performed on the basis of information gathered when the user has been identified by an internal system, other information from the internal system or other external systems, the observed behaviour of the user and/or preferences expressed by the user.
  • the internal system uses exchangeable algorithms from a first set of algorithms in order to analyse the user's behaviour and govern group affiliation divi- sion.
  • the system can automatically test various information presentations and register the outcome, and alter the group affiliation division for a user in order to refine the group affiliation division for a user.
  • the invention enables the behaviour of different users to be ascertained, thereby enabling the layout of information services to be optimised.
  • the design of the invention ensures that the system reacts extremely quickly to a user's behaviour or preferences. Already after one user visit the system can provide the user with a relevant group affiliation.
  • the invention is independent of technical platforms and can deal with environments in which different media and platforms are mixed.
  • Figure 2 shows how the user's group affiliation is assigned using information from various sources and information from the internal system
  • Figure 3 shows how the system compares a user's behaviour with predetermined behaviour for group affiliation stored by the system.
  • the present invention relates to a method for assigning users a group af- filiation.
  • Figure 1 is intended to show that the first step is for the user 9 to be identified 1 with the aid of user information from either an external system or an internal system 2.
  • the user is assigned a group affiliation 6 with the aid of exchangeable algorithms from a first set of algorithms 4 and possibly information from external sources 5 and user information 2.
  • An analysis is per- formed of the user's documents 7.
  • the result of the analysis updates 8 the user information 2, A and/or the exchangeable algorithms 4, B.
  • the internal system 1 identifies 10 the user 9 with the aid of the informa- tion supplied by the medium used or by the user himself stating his identity, as shown in Figures 1 and 2. Cookies, ip numbers, etc. can be used for web readers on the Internet. Further information from other external sources may also be used 5.
  • the internal system uses databases 4 to store information about the individual users, such as identification information, implicitly and explicitly produced prefer- ences and behaviour. The databases are used, for instance, at identification.
  • the next step is for the individual user to be assigned group affiliation where the presentation of information is controlled.
  • the internal system uses a control algorithm 3 to select differentiation algorithm 4.
  • the control algorithm chooses between several different differentiating algorithms in accordance with criteria dictated in the control algorithm, e.g. date.
  • the differentiating algorithm selected can use information from the user database 2 about the user's preferences or behaviour and/or information from other sources 5. No limits exist as to the type of data source.
  • the differentiating algorithm selects a group affiliation 6 and thus also a presentation for the user concerned.
  • the relevant regulation, other information from the user database or other sources and selected presentation are stored in a session object, a sustainer.
  • a presentation may be a reference to an informa- tion source, e.g. a URL.
  • the internal system supports an unlimited number of presentations.
  • a quantity of system parameters also pertain to the presentation, their values varying depending on which presentation is used.
  • the stored events indicating interest shall be combined with the existing user information. This is performed by the updating function 8 which updates the behaviour and preferences A of the individual user and/or the exchangeable algorithms 4, B.
  • An exchangeable algorithm from a second set of algorithms 12 compares the user's stored behaviour and preferences 11 with one or more predetermined behaviours and preferences 6 in order to select one of the presentations.
  • the predetermined behaviours and preferences may be influenced by other data sources and may be changed in real time.
  • Variable probabilities In accordance with various probability values the algorithm distributes the users to the various presentations in combination with the use of user-segmented differentiation, for instance.
  • Single-optimisation the algorithm distributes the users to the various presentations in combination with the use of user-segmented differentiation, for instance.
  • the algorithm distributes the users stochastically between two or more presentations.
  • the algorithm measures the differences in outcome over a predetermined period of time between the various presentations, and selects the best presentation after the predetermined period of time to all users.
  • the algorithm distributes the users either stochastically or via predetermined behaviours and preferences between a first set of different presentations.
  • the user's outcome is analysed on the basis of a set of desirable outcomes and a second set of presentations is used.
  • the possible number of levels of presentations and desired outcomes is unlimited.
  • the user-behaviour is stored in database records that can be likened to vectors.
  • Each information object has one or more vectors of its own in which the agreement of the product with various segmented properties is stored.
  • each user has a vector for each type of vector the information objects have, with the same appearance as regards data field. This is to enable comparison of the user's set of vectors with that of the information objects, which results in a deviation point. Less points indicate less deviation and thus an information object that matches the user better.
  • the database contains a table for each type of information object vector and a table for each type of user vector.
  • the appearance of different segmenting properties for the vector in, for instance, a system where cinema tickets are to be sold may be for an information object (an individual film): Action, Romance, Drama, Family, Thriller, Science- fiction.
  • the information object usually has binary values for the various categories.
  • the user has a similar vector where the fields contain liquidity index values which are constantly updated depending on which information object the user has been exposed to or has chosen.
  • the liquidity index values can be interpreted as probabilities indicating the user's tendency to choose a specific information object.
  • Sessions-sustainer Each user's set of vectors, specific settings for the differentiation and settings for methods as to how deviation points between the user's sets of vectors and the information object's sets of vectors shall operate must be retained during a visit for each individual user since this quantity of data is frequently required by the system.
  • a method is also needed for storing the interest shown by the user for information objects. Two forms of interest are usually displayed by the user: exposure or purchase of an information object. Other forms of interest indications events may exist dependent on the implementation in question, but these two are typical examples.
  • the system uses two types of sessions-sustainers. These are objects which, depending on implementation, can use the server's RAM memory, for instance, or a database schedule to store information.
  • One sort of sustainer is used to store the user's set of vectors and settings for the visit, while the other sort stores information about interest displayed by the user.
  • a general interest-sustainer shall have methods for creating an object, linking this to a particular visit session, which is identified with a unique text string or a number, and for storing the event "exposure” of an information object and storing the event "purchase” of an information object. The time shall also be saved upon storing.
  • the present invention also relates to a computer program product comprising computer program codes which, when executed by a computer, is designed to perform necessary operations to assign a user a group affiliation in accordance with the method of the invention.
  • the present invention also relates to a carrier medium, that carries computer program codes in accordance with a computer program product of the invention, as well as a medium readable by a computer, in which computer program codes in accordance with the invention are stored.

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  • Business, Economics & Management (AREA)
  • Strategic Management (AREA)
  • Engineering & Computer Science (AREA)
  • Accounting & Taxation (AREA)
  • Development Economics (AREA)
  • Finance (AREA)
  • Economics (AREA)
  • Game Theory and Decision Science (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Marketing (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • Two-Way Televisions, Distribution Of Moving Picture Or The Like (AREA)

Abstract

La présente invention concerne un procédé permettant d'adapter l'information au comportement ou aux préférences d'un utilisateur. Cette adaptation se réalise par optimisation automatique. En l'occurrence, une fois que l'utilisateur est identifié, un groupe d'appartenance lui est affecté. La sélection de l'information se fait sur la base de ce groupe d'appartenance. Le comportement et/ou l'historique de l'utilisateur considéré fait l'objet d'une analyse dont les résultats, ainsi que d'autres informations disponibles, servent à resserrer le champ de sélection de l'information pour cet utilisateur.
PCT/SE2001/001636 2000-07-20 2001-07-16 Adaptation de l'information au comportement ou aux préférence d'un utilisateur par optimisation automatique Ceased WO2002008991A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
AU2001271217A AU2001271217A1 (en) 2000-07-20 2001-07-16 A method for adapting information to suit a user's behaviour or preferences withautomatic optimisation

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
SE0002727A SE0002727L (sv) 2000-07-20 2000-07-20 Metod för att anpassa information efter en användares beteende eller preferenser med automatisk optimering
SE0002727-6 2000-07-20

Publications (1)

Publication Number Publication Date
WO2002008991A1 true WO2002008991A1 (fr) 2002-01-31

Family

ID=20280555

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/SE2001/001636 Ceased WO2002008991A1 (fr) 2000-07-20 2001-07-16 Adaptation de l'information au comportement ou aux préférence d'un utilisateur par optimisation automatique

Country Status (3)

Country Link
AU (1) AU2001271217A1 (fr)
SE (1) SE0002727L (fr)
WO (1) WO2002008991A1 (fr)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11842379B2 (en) 2022-02-18 2023-12-12 Sas Institute Inc. Method and system for obtaining item-based recommendations

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1999008214A2 (fr) * 1997-07-25 1999-02-18 Øtr Økonomisk Transaksjons Reklame As Systeme d'affichage d'informations sur des automates transactionnels decentralises
EP0902383A2 (fr) * 1997-09-10 1999-03-17 Ncr International Inc. Réseau de communication
WO1999062012A1 (fr) * 1998-05-22 1999-12-02 Cambridge Consultants Limited Systeme de communications electroniques
WO2000017793A1 (fr) * 1998-09-18 2000-03-30 Amazon.Com,Inc Utilisation de cartes d'achats electroniques pour elaborer des recommandations personnelles
EP1050832A2 (fr) * 1999-05-05 2000-11-08 Xerox Corporation Méthode pour trouver des groupes de personnes basée sur le contenu analysable linguistiquement de ressources accédées

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1999008214A2 (fr) * 1997-07-25 1999-02-18 Øtr Økonomisk Transaksjons Reklame As Systeme d'affichage d'informations sur des automates transactionnels decentralises
EP0902383A2 (fr) * 1997-09-10 1999-03-17 Ncr International Inc. Réseau de communication
WO1999062012A1 (fr) * 1998-05-22 1999-12-02 Cambridge Consultants Limited Systeme de communications electroniques
WO2000017793A1 (fr) * 1998-09-18 2000-03-30 Amazon.Com,Inc Utilisation de cartes d'achats electroniques pour elaborer des recommandations personnelles
EP1050832A2 (fr) * 1999-05-05 2000-11-08 Xerox Corporation Méthode pour trouver des groupes de personnes basée sur le contenu analysable linguistiquement de ressources accédées

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11842379B2 (en) 2022-02-18 2023-12-12 Sas Institute Inc. Method and system for obtaining item-based recommendations

Also Published As

Publication number Publication date
SE0002727L (sv) 2002-02-04
AU2001271217A1 (en) 2002-02-05
SE0002727D0 (sv) 2000-07-20

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