EP1346297A1 - Procede et systeme d'extraction d'informations - Google Patents

Procede et systeme d'extraction d'informations

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Publication number
EP1346297A1
EP1346297A1 EP01919771A EP01919771A EP1346297A1 EP 1346297 A1 EP1346297 A1 EP 1346297A1 EP 01919771 A EP01919771 A EP 01919771A EP 01919771 A EP01919771 A EP 01919771A EP 1346297 A1 EP1346297 A1 EP 1346297A1
Authority
EP
European Patent Office
Prior art keywords
agent
user
value
match
module
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
EP01919771A
Other languages
German (de)
English (en)
Inventor
Guido Braccini
Salvatore Manzi
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.)
Hi - Flier Srl
Original Assignee
HI FLIER SpA
Hi-Flier SpA
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 HI FLIER SpA, Hi-Flier SpA filed Critical HI FLIER SpA
Publication of EP1346297A1 publication Critical patent/EP1346297A1/fr
Ceased legal-status Critical Current

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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
    • G06Q30/06—Buying, selling or leasing transactions

Definitions

  • the present invention refers to a method of stored information retrieval through a single computer or distributed between more computers connected to a telecommunication network. In particular, this refers to meeting or "matching" services between the users that employ intelligent agents.
  • the term user means either a physical person or an informative system that operates in the environment of a matching service.
  • an intelligent agent or, more concise, an agent is a software entity, that is a computer program, which has the ability to move freely within a particular environment and the ability to make decisions simulating human behaviour in order to achieve the user's goal.
  • the agents to which the present invention refers operate with structured data, that is data that, unlike unstructured data, present a value and a label that explain the significance of the data.
  • agents have the following characteristics :
  • - Reactivity that is the characteristic to react to changes in the environment in which they operate
  • - Proactivity that is the characteristic to take initiative while interacting with the external environment
  • intelligent agents make them appear particularly interesting instruments to face problems regarding information retrieval and processing and, in particular, distributed information.
  • intelligent agents find favourable applications while retrieving and processing information on the INTERNET network, where the selection of information is more difficult because of the continuous increase in the quantity of information that is available on said network.
  • search engines employ (for example, available "on-line” on the INTERNET) or methods using "databases" or local storage systems.
  • Conventional search engines can operate with both unstructured data and structured data, while databases contain information stored in a structured way.
  • a user can insert key words corresponding with the appropriate web pages and the search engine, by means of a program named "spider", returns the user a list of links to web pages corresponding to the inserted key words.
  • a user can fill in suitable search forms selecting preferences and launch programs, for example, CGI (Common Gateway Interface) programs, which carry out queries in the database and return the searched information to the user.
  • CGI Common Gateway Interface
  • databases and on-line search engines produce an excessive number of results (for example, an excessive number of links) that only partly facilitates the operation of information retrieval;
  • the consumer and the provider are provided with a respective intelligent agent.
  • the intelligent agent associated with the consumer can create decision- making agents that go shopping and assist the consumer in buying products.
  • the intelligent agent associated with the provider can create agent-requests that quantify the request and the goal of a specific consumer.
  • the possibility to use several intelligent agents associated with one single provider and with one single consumer facilitates the retrieval and the exchange of market information and represents a support for electronic commerce.
  • Conventional methods do not allow the creation of services that enable users satisfaction for users that have requirements typical for a requesting user and requirements typical for an offering user at the same time.
  • a particular example of such services is that of meeting between people. In this case the first user looks for a second user that meets some requirements yet, at the same time, the meeting can only be considered concluded if that first user also meet the second user's requirements. Therefore, conventional methods show a lack of generality in the type of services to which they refer.
  • the object of the present invention is to propose a method for information retrieval employing intelligent agents that surpasses the limits of application described above with regard to the known techniques.
  • a part of the present invention is a computer program directly loadable into the central memory of a processing system and a system for the retrieval of information available from at least one computer.
  • FIG. 1 schematically shows a particular embodiment of a computer system for carrying out matches in accordance with the present invention
  • FIG. 2 schematically shows an example of hardware/software system architecture for information retrieval in accordance with the present invention and that can be implemented in the system in figure 1;
  • - figure 3 shows in more detail some modules contained in the system of figure 2;
  • - figure 4 shows some steps of an embodiment of a method according to the invention by means of a flow chart ;
  • - figure 5 schematically indicates the types of data managed by the system in figure 2;
  • FIG. 6 illustrates a particular structure of data of an agent in accordance with the present invention
  • - figure 7 represents the agent type datum
  • - figure 8 illustrates the data structure of a matching item
  • - figure 9 schematically illustrates an example structure of one of the features of a matching item in figure 8;
  • - figure 10 shows an example dialog box that can be used by an administrative user (henceforth called “system administrator” or simply “adminstrator” ) in order to carry out implicit coding in accordance with this invention;
  • - figure 11 shows a further dialog box that can be used by an administrator;
  • FIG. 12 illustrates the structure of a matching category data
  • - figure 13 shows a dialog box that represents the tree structure of the categories;
  • - figure 14 illustrates the structure of a comparison function that can be used according to the invention;
  • - figure 15 shows the data structure of a comparison rule
  • - figure 16 schematically shows a diagram representing an example of an agent's life cycle in accordance with this invention
  • - figure 17 shows a dialog box that can be used by the administrator to configure an agent's timing
  • - figure 18 schematically shows a flow chart related to the method in accordance with this invention
  • - figure 19 shows a dialog box that can be used by an administrator in order to carry out explicit coding.
  • the method in accordance with this invention allows the retrieval of an information in order to provide it to a first user, so as to satisfy a predetermined goal.
  • This information is selected from information stored in at least one computer and associated with one or more users .
  • information retrieval according to the goal can be defined as search for a meeting or "match" between the first user and a second user the information is associated with.
  • matching services to which the method of this invention apply are: financial services, wireless services, electronic commerce services, job search services, people meeting services, news services, booking services, resource allocation and search engine services.
  • a financial service can be defined as matching financial products with investors' profiles.
  • a wireless service can be defined as the search for services distributed by a wireless device (for example a mobile telephone) in accordance with the profile of user owning it.
  • Electronic commerce takes place in a "market" that is the environment in which sellers that offer products want to meet buyers that request products.
  • the requested match is that between companies that are looking for personnel and possible candidates, while in people meeting services both sides look for people's specific profiles.
  • news services interesting news are to be retrieved for the user and then made available to the user.
  • Booking services may concern hotels, shows etc. while resource allocation services allow the distribution, for example, of human resources to companies .
  • Search engine services aim at carrying out a match between key words and a structured representation of a digital document .
  • matching services to which we refer allow the matching between available information in at least one computer, that is stored in a database of a single computer and/or distributed into a telecommunications network.
  • matching system 100 that can be employed in this invention.
  • Matching system 100 comprises a telecommunication network 101 such as, for example, an INTERNET (INTERnational NETwork) network.
  • a telecommunication network 101 such as, for example, an INTERNET (INTERnational NETwork) network.
  • INTERNET INTERnational NETwork
  • INTERNET is a global network of computer systems with a decentralised structure.
  • INTERNET computer systems use a client/server architecture, in which a remote computer system (server) supplies a local computer system (client) with information and services.
  • server remote computer system
  • client local computer system
  • INTERNET considers various access protocols; in particular, the World Wide Web
  • WWW HyperText Markup Language
  • HTML HyperText Markup Language
  • telecommunications network 101 can also comprise "wireless" systems such as, for example those systems employing WAP technologies (Wireless Application Protocol), UMTS (Universal Mobile Telecommunication System) or any other technology that allows access to the INTERNET network, also by means of mobile telephones, handheld computers, or PDA (Personal Digital Assistant) , which hereafter will be synthetically referred to as “wireless technologies” .
  • WAP technologies Wireless Application Protocol
  • UMTS Universal Mobile Telecommunication System
  • PDA Personal Digital Assistant
  • matching system 100 comprises, in conjunction with the telecommunication network 101, a server computer system SI, a remote server computer system S2 and a plurality of client computer systems comprising two client computer systems CI and C2.
  • Server computer system SI can comprise various server computers intended for particular functions .
  • Matching system 100 can be used by a plurality of users Ui to which a first user Ul and a second user U2 belong .
  • first user Ul and second user U2 are respectively associated with client computer systems CI and C2, hereafter for conciseness named client systems CI and C2.
  • the other users of the plurality of users Ui can use the respective client systems or they can connect to network 101 by means of a wireless interface, for example, by means of a mobile telephone.
  • server computer system With reference to figure 1, server computer system
  • a processing unit PU controls the functioning of a computer server SI
  • a central memory 215, typically a DRAM (Dynamic Random Access Memory) is directly used by processing unit PU
  • a read only memory (ROM) 220 contains a base program for the bootstrap of the same computer system.
  • Client computer systems CI and C2 like personal computers, also comprise various peripheral units (not shown) .
  • peripheral units not shown
  • they comprise a mass memory consisting of a hard disk, a drive for optical discs
  • CD-ROM compact disc-read only memory
  • client computers CI and C2 comprise (not shown) a respective input unit consisting of a keyboard and a mouse, a respective output unit consisting of a monitor and a printer, and a MODEM ( "MOdulator DEModulator” ) for the connection to telecommunication network 101.
  • a respective input unit consisting of a keyboard and a mouse
  • a respective output unit consisting of a monitor and a printer
  • a MODEM "MOdulator DEModulator”
  • the method in accordance with this invention plans to associate an intelligent agent AGi, more concisely an agent AGi, with every user Ui.
  • the goal of each agent is to carry out a match with another agent in accordance with a predetermined goal .
  • an agent besides the characteristics previously defined (autonomy, reactivity, proactivity and social abilities) can, optionally, be created in such a way that it presents the following optional characteristics:
  • each server system SI and S2 represents a platform for intelligent agents, that is an environment in which intelligent agents can operate.
  • the intelligent agents are of a mobile type, they can move from one environment to another, and therefore the server systems SI and S2 connected through network 101 represent a peer-to-peer network for the agents. It is worth noting that in such a case, the software related to an intelligent agent is implemented with a code that is not intended to operate or run only in one computer (for example, one of the servers) , but it is able to move from one server system to another and operate also when the server system of departure is disconnected. However, the findings of this invention are applicable both to mobile intelligent agents and to intelligent agents that do not have this characteristic.
  • Agent AGi during its "life cycle", can change state, taking on from time to time one of the defined states.
  • FIG 2 an embodiment of a system 200 for information retrieval in accordance with the present invention is shown.
  • system 200 is suitable for being implemented in matching system 100 as described above.
  • This system 200 operates by means of the search of matches between intelligent agents. That is, it provides a matching service between users Ui by looking for a match between agents AGi associated with these users .
  • System 200 is represented in figure 2 by means of functional blocks that can be interpreted at the same time as the hardware components of one or more processing systems or as their software modules.
  • the software corresponding to system 200 can be loaded into central memory 215 of server computer system SI described with reference to figure 1.
  • System 200 comprises a main unit made up of a matching engine module ME (henceforth engine module ME) and a plurality of subsystems and sub-modules to which it is connected.
  • the plurality of sub-modules is subdivided into a plurality of server sub-modules, a plurality of client sub-modules and a plurality of peer sub-modules according to the type of relation existing between it and engine module ME.
  • the plurality of client sub-modules comprises a management module EMM of engine module ME and an optional affiliation tool TM that allows the insertion of intelligent agents from an external database.
  • the plurality of server sub-modules comprises a database or local storage system LDB, an optional external database EDB (connected to the engine module ME by means of a connection module EDBC) , a notification manager module NM in its turn connected to a plurality of server communication modules, intended for communicating the matching results of their respective agents to the users by means of any channel of communication.
  • this plurality of communication modules comprises a module MM for the management of electronic mail, a module SMSM for the management of SMS messages (Short Message Service) , a module VMM for the management of voice mail .
  • the notification manager module NM is also connected to logging module LM.
  • the plurality of peer sub-modules can comprise one or more remote engine modules RMEs, analogous to engine module ME and a user interface module IUM connected to a graphical interface module GIM for web systems and a wireless system interface module IWM.
  • connection lines 201 that present a single arrow set on an end indicate that between the two connected modules there is a “client to server” relationship, corresponding to which the arrow is placed in the end near the server module.
  • those lines 201 having arrows at both ends indicate that the two connected modules constitute two peer units, a "peer to peer” relation.
  • the engine module ME and the remote engine module RME communicate with each other, forming a peer connection. This allows the engine module ME to extend the environment in which agents operate also with remote engine modules RME, creating in this way the same functionality of agents which have the optional characteristic of mobility defined above.
  • Engine module ME principally has the function to manage the life of intelligent agents AGi, receiving commands that it redistributes to these agents .
  • This engine module ME from a hardware point of view, can be implemented with processing means, that is processing unit PU of server system SI in figure 1.
  • engine module ME manages messages transmitted or received to/from other modules to which it is connected and searches for a match between one agent and another.
  • this engine module ME can be implemented as a C++ object.
  • engine module ME can take on both a server or a client mode according to the other modules to which it is connected, or it can have a peer to peer relation with them.
  • all the commands received in the server mode and sent in the client mode and all the replies received in the server mode and sent in the client mode are XML messages (extensible Markup
  • Management module EMM is an administration tool of system 200 and allows the administrator to configure system 200 before the end-users use it and it allows the examination and monitoring of system 200 while it is running. In particular, management module EMM allows the configuration of an agent structure.
  • affiliation tool module TM allows to create agents in a systematic way on the basis of appropriate tables containing information concerning the agents and stored in an external database.
  • the agents created in this way can be launched in batch mode in order to carry out a match.
  • Local database LDB is an example of storage means in which, among other things, all data related to the users using matching system 200 and all data that allow the definition of intelligent agents associated with these users can be stored.
  • External databases EDB can store data related to users, however structured in a different way from the local database LDB for which engine module ME is configured.
  • Connection module EDBC created, for example, with a commercially available data mapping module allows to carry out the mapping of data by converting their structure into a structure which is compatible with engine module ME.
  • User interface module IUM is a module that can carry out both the server and the client mode and serves to interface engine module ME with a user, understood either as a person (customisation function) or as a data source of a information system (integration function) .
  • this module IUM can send commands to engine module ME calling functions belonging to an appropriate API (Application Programming Interface) library.
  • API Application Programming Interface
  • User interface module IUM also shows a server behaviour, making specific functions available for other modules. The most important functions are the ones destined by engine module ME to synchronise (i.e. update) agents' structured data, which are present both in module IUM and in module ME and that are updated first in module ME and subsequently in module IUM.
  • user interface module IUM provides an interface with users who use web-based systems and/or wireless systems.
  • the user has an interface program at his/her disposal, both in the browser of the computer and in the microbrowser of a wireless device, with which he/she carries out the operation of agent browsing and insertion, and the visualisation of the matching results of his/her agent.
  • HTML pages or WML pages (Wireless Markup Language) - or other forms of graphical interfaces - visible to the user can dynamically be generated in all or in part from information taken from engine module ME with or without the help of API library functions.
  • FIG 3 shows the place of the API and the proprietary tags in the architecture.
  • engine module ME connected to local database LDB, communicates with module API, containing the API functions, by means of XML messages.
  • Module API can be replicated in management module EMM and in affiliation tool module TM in order to allow their communication with engine module ME.
  • Management module EMM is equipped with graphical interface module GUI-A for the administrator.
  • IUM user interface model
  • ISM interface module
  • User interface module IUM communicates with graphical interface module GIM (for web systems and an interface module with wireless systems IWM.
  • User interface module ISM with an information system type user, also communicates with a platform SPP, which represents the information system to which the functionalities of this invention are added.
  • This module ISM is, for example, implemented in Java.
  • tag library LTG which, as mentioned above, allows the construction of user interface module IUM by means of the definition of propriety tags.
  • notification manager module NM is a server that allows the sending of notification messages of match occurrances to a user. Such messages can be sent through what ever communication channel preferred (for example, by means of electronic mail, SMS messages or voice mail) . Therefore notification manager module NM collaborates with the corresponding server module of the specific communication channel used; for example, module MM for the management of electronic mail, module SMSM for the management of SMS messages or module VMM for the management of voice mail.
  • Logging module LM allows to log information concerning all actions undertaken by engine module ME and by notification manager module NM in a local database . By means of engine module ME management module EMM can access the logging module with the aim of monitoring the history of actions and other state parameters of module ME.
  • Remote engine module REM can be, for example, implemented in remote server system S2 of figure 1 while the other modules of figure 2 can be implemented in server system SI. Users Ui can connect to server system SI by means of client systems CI and C2 or by means of wireless devices.
  • the method in accordance with this invention associates an agent AGi with each user Ui .
  • agent AGi For example, let us consider the case in which user Ul is associated with agent AGl and user U2 is associated with agent AG2.
  • the required match is to achieve a predefined goal that takes the needs of the first user, Ul, and of the second user, U2, into account.
  • the method contains a data inserting step INSER-DATA according to which a first value R-1 requested by user Ul and a first value 0-1 offered by user Ul are associated with agent AGl.
  • a second value R-2 requested by user U2 and a second value 0-2 offered by user U2 are associated with at least agent AG2. This kind of association can be carried out for a part of or for all agents AGi that have been taken into consideration.
  • match searching step ELAB-MATCH comprising the processing of the values associated with first agent AGl and second agent AG2.
  • This match searching step ELAB- MATCH can be repeated for each agent AGi .
  • Such processing provides an affinity indicator between first agent AGl and second agent AG2, corresponding to the goal of matching.
  • processing comprised in step ELAB-MATCH provides a real number relating to the satisfaction of both users Ul and U2 and resulting from the match between agents AGl and AG2.
  • the method comprises a notification step
  • NOTFYCATION according to which one of the users Ul, U2 or both of them are notified of the match and are provided with the searched information.
  • the method finishes with final step ENDM.
  • system 200 can be seen as an environment containing a set of categories S-C, of agent types S-AGT, of matching items S-MI, of features S-F, of data types S-DT, of comparison functions S-CF, of comparison rules S-CR and of agents S-AG.
  • agent AGi can be seen as a plurality of feature/value (s) pairs that form an unordered list.
  • the structure of an agent AGi can be subdivided into system features SYF and matching item features MIF.
  • a set of features MIF and a set of agent types AGT is meant with the term matching item MI.
  • matching feature MI can be a product, for example, a chair, and two possible matching item features MIF could be the colour and the price of the chair.
  • agent types AGT are a Seller agent and a Buyer agent .
  • agent type AGT is a representation of name NME of the agent type, for example Seller, Intermediary, Buyer, Person.
  • the administrator can choose which pair of agent types, in the set of agent types S-AGT, is to be enabled for matching a specific matching item MI. For example, in the case of electronic commerce, it is possible to decide that a Buyer agent and an Intermediary agent can be authorised to make a match on a product, while it can also be decided that such a match will not be allowed for a Seller agent and a Buyer agent.
  • FIG 8 illustrates the data structure of a matching item MI comprising a name MI-N, a set of matching item features S-MIF and the set of agent types S-AGT.
  • a flag FLGji whose value indicates the possibility or the impossibility (enabling/disabling) of carrying out a match between agent types AGTj and AGTi. For example, when the flag is set to 1, the matching is allowed while when the flag is set to 0, matching is not allowed.
  • system features SYF are shared by every agent AGi and are: start date SD; end date ED; agent type reference AGT-R; user reference U-R, matching item reference MI-R.
  • Start date SD represents the date of birth of agent AGi, that is to say that this agent is enabled for matching only after this date.
  • agent AGi is "locked" (locked state) .
  • End date ED represents the date beginning from which agent AGi is considered to be in a "dead state" , that is, after that date agent AGi can not carry out a match anymore.
  • Agent type reference AGT-R will have a value that can be selected from a list of agent types associated with matching item MI.
  • the features concerning a product can be associated with a Buyer agent or a Seller agent, or when the matching service concerns people meeting, the corresponding agents are Person agents.
  • User reference U-R is a datum that points to user Ui with which agent AGi is associated and it points to the user's personal data.
  • Matching item reference MI-R is a datum that points to matching item features MIF.
  • Matching item features MIF can vary from agent to agent .
  • a set of agents is typically sectioned in such a way that agents of the same section point to the same matching item.
  • Matching features MF unlike those of an auxiliary type AF, are directly involved in processing carried out for matching search.
  • requested values R are used in the processing related to the matching search.
  • Generic requested value Rj is a value that can be interpreted from a logical point of view as a search request of a complementary offer.
  • the generic offered value Oj is a value that can be interpreted as an offer for which a complementary request is searched. In the case in which the matching feature is interpreted as both a request and as an offer or as neither of them, the value of offered value Oj is equal to the requested value Rj and this value is defined as "neutral" .
  • User preference UPj is a number, for example an integer within the interval [0,100] that the user can associate with requested value Rj of a matching feature MFj .
  • User preference UPj represents the level of dissatisfaction of user Ul associated with agent AGl when the distance between requested value Rl and offered value 02 of agent AG2 increases. In particular, it can decided that the greater is user preference Upj the higher is the user's level of dissatisfaction.
  • each auxiliary feature AFj and each matching feature MFj comprise a plurality of components.
  • the components of a matching feature MFj are: name N, data type DT, indicator of auxiliary flag AF.
  • different components are defined: request visibility VIS-R and offer visibility VIS-O, neutral visibility VIS-N, mandatory request MA-R and mandatory offer MA-O, neutral obligatoriness MA-N, a priori preference APP and can- state preference CAP.
  • figure 9 refers to to a number equal to "s" of pairs MI-R and AGT-R.
  • Name N is a component that allows to point to features; for example, an offered feature could have a name like colour, age, sex etc.
  • Visibility is a component that can take on a Boolean value (0 o 1). For example, when the visibility is set to 1, it means that the corresponding feature is visible for the user by means of an appropriate interface, when the user creates his/her agent him/herself, while in the case of a visibility set to 0, the feature is not visible.
  • Request visibility VIS-R allows the user to insert
  • the interface that allows the user to insert the feature value consists of a graphical control, for example, a text box.
  • Neutral visibility VIS-N indicates that a unique graphical control must be visible to allow to insert a value, which is logically interpretable both as an offer and as a request.
  • feature "age” can alternatively be:
  • this interface will be different according to these two data structures. For example, in the case of electronic commerce, we will have two different graphical interfaces for two different products (a product is a matching item) and, having the same product , a different interface for the launch of Buyer agents and Seller Agents .
  • the obligatoriness component (MA-R, MA-O, MA-N) can take on a Boolean value (0 or 1) and when it is set to value 1, it means that the feature, made visible in the way described above, must be filled by the user, while when it is set to 0, the corresponding feature is not mandatory for the user.
  • a priori preference APP is a component expressed by means of a number, for example, an integer within an interval [0,100] that the system administrator can associate with request value R of a matching feature MF.
  • a priori preference APP has a meaning which is analogous to that of user preference UP above defined, yet it is not predetermined by the user, but it is inserted by the administrator.
  • a priori preference APP is combined with user preference UP above described according to the modes that are described further on.
  • Can-have preference CAP can take on a Boolean value (0 or 1) and, when it is set to 1, it means that the user can set user preference feature UP when he or she creates agent AGi, while this feature UP can not be set if can-have preference CAP equals 0.
  • Auxiliary feature flag (AF) can take on Boolean values 0 or 1. When it is set to value 1, components APP and CAP lose significance, while visibility and obligatoriness are not expressed in components VIS-R, VIS-O, VIS-N e MA-R, MA-O, MA-N anymore, but they respectively consist only of a component that indicates visibility and the obligatoriness of the auxiliary features. For example, in figure 9 the meaning of the individual flags can respectively be taken on by VIS-O and MA-O. If the component AF is equal to 0, the feature MFj is a matching feature in the sense described above.
  • Data type DT is a component of matching feature MFj that associates with a matching item feature MIF a domain or a number of values that matching item feature MIF can take on both in request and in offer. Data type DT differs because of the type of inserted values related to that feature.
  • the user can insert only one value or a list of k values
  • the value can be chosen in a set of predefined values F or in an infinite set I;
  • the value can be a number N or a string S .
  • possible DT data types which are determined according to the three cases described above, are defined and listed.
  • the data type is a Set of Predefined Strings.
  • the set of Predefined Strings "C” , "C++” is an example of this data type.
  • An example of a Set of Predefined Numbers is the datum: 39,40,42.
  • An example of Single Predefined String is the string "foo" .
  • the other data types of Table 1 are clear because of their name and corresponding definitions.
  • vectors of real numbers can be associated with the same number of values of data types Single Predefined String and Set of Predefined Strings through a coding operation.
  • Each vector component is associated with a numerical sub-feature.
  • the data type Single Predefined String and Set of Strings are further divided into Coded and Uncoded.
  • coded the calculation of the semantic distance is traced back to a vector distance.
  • Predefined Uncoded String or from a Set of Predefined Uncoded Strings associates a Single Predefined Coded String or a Set of Predefined Coded Strings respectively, can occur according to an explicit or an implicit method.
  • Table 2 shows an example of explicit coding for a feature "sport", where a vector with sub-features, that can assume the value 0 or 1 depending on the sub- feature, is associated with each string representing a sport .
  • the administrator can open a window in which the string values are represented as icons displayed on the window area.
  • the system administrator can drag these icons, placing them at a relative distance which represents the semantic distance of these values.
  • the two-dimensional coordinates of these points are the values of the sub- features composing the vector.
  • Figure 10 shows an example of COD-WINDW dialog box which can be used by the administrator to carry out the implicit coding in the aforementioned case.
  • Figure 10 four squares concerning the four job positions CEO, COO, CTO, CIO are illustrated and a cursor 300 is shown, using which it is possible to drag each square to a position considered representative of the semantic distance separating a job position from the others.
  • Implicit coding is especially useful when an explicit coding is difficult to carry out. Moreover it enables the integration with natural language processing systems which have two-dimensional maps of words as output.
  • the window of figure 10 comprises also an OK button to confirm, a Cane button to delete, and a conventional button 400 to close the window itself.
  • Another data type which can be used to process strings is the one in which the administrator directly provides a measure of the distance for every string pair filling a square matrix whose rows and columns correspond to the strings. It is a valid method for the distances among towns, for example, and for the integration with natural language processing systems, which have the distance among string pairs as output.
  • This data type will be named "Single Predefined Related String” and "Set of Predefined Related Strings” .
  • Figure 11 shows a window available to the administrator to create this data type on a display, such as a monitor (not shown) of a computer used by the administrator.
  • the window of figure 11 shows a square matrix on whose rows and columns the following strings, indicating different company departments, are shown: Wireless Infrastructure, "Wirelss-Infrastrcut” ; Hardware and Software, “HW and SW” ; consulting, “Consultng” ; Application Service Provider, “Appl-Servce-Provd” ; Wireless Telecommunications "Wirelss-Telcommn” .
  • the value of the semantic distance between the compared departments is shown by the intersecting matrix cells.
  • the matching items (made up of an unordered list containing the matching item features MIF) are advantageously grouped in categories and sub- categories according to the sector the matching refers to.
  • the category CATRY can be seen as comprising a name of CAT-N category, a set of references to sub-categories or other categories S-C and the set of references to the matching items S-MI.
  • the grouping into categories and sub- categories presents a tree structure.
  • this tree structure is analogous to that used in the representation of icons of folders (directories) in the GUI of operating systems such as Windows.
  • figure 13 illustrates a structure management window STRUCT-MNG visible to the administrator.
  • This window shows a meeting category MEET and a category "e-commerce” .
  • the e-commerce category does not contain any sub-categories but contains the matching items Computer, "CDs", “Book”.
  • the Book matching item contains the features "Price”, “Language”, “Title” , "Author” .
  • the window of figure 13 presents a CREAT-CATRY button for the creation of categories, a CREAT-MI button for the creation of matching items, an ADD-FEAT button for the addition of features. The selection of these buttons allows the administrator to create a category, a matching item or a feature respectively.
  • the window of figure 13 comprises conventional buttons 400.
  • the processing step ELAB-MATC comprises the processing of the values associated with the agents Agi according to comparison functions CF, described below.
  • a comparison function CF has a name CF-N and operates on two arguments which are of two equal or different data types.
  • the comparison function operates on an offered value O of a first agent together with a requested value R of a second agent and gives a real number as result.
  • This result shows how much the offered value O complies with the request R. For example it can be said that the user's satisfaction associated with the agent is greater if the real number resulting from the comparison function CF is lower.
  • the matching will occur in relation to an agent for which the comparison function result is null.
  • Comparison functions are subdivided into comparison functions with homogeneous features and comparison functions with heterogeneous features according to whether they operate on requested values R and offered values O belonging to equal features of the same matching item (homogeneous features) or different features of two different matching items (heterogeneous features) .
  • the comparison functions with homogeneous features can be of different types according to the data type they apply to. Some examples of comparison functions which can be selected for some data types are given below. In the case of Single Predefined Numbers or of Single Numbers, the comparison functions can be:
  • f (R,0) abs (R-O) /max(R,0) ;
  • f (R,0) l-number of common characters between R e O /max (number of common characters of R, number of characters of O)
  • f (R,0) number of elements common to R and 0 can be used.
  • the heterogeneous features are used to compare two different features of the same matching item or of two different matching items. An example could be where the requested value R is of a feature of type "Single Number" and the offered value O is a value of a feature with "Single Predefined Coded string" data type.
  • comparison rule CR presents a data structure shown by way of example in figure 15. According to this comparison rule CR the agents referring to the agent type Agtl and the matching item Mil are enabled for matching with the agents of the type AGT2 and of the matching item MI2, using the comparison function CF* to compare the matching item features of the matching items MF1 and MF2.
  • comparison function CF is homogeneous, that is the values of the two arguments refer to the same feature of the same matching item.
  • the information associated with a user Ui can be sent to the local database LDB by the user through the user interface IUM.
  • the data structure configuration described above can be carried out by means of the management module EMM.
  • EMM management module
  • a bank manager will define the most suitable data structure for the specific context.
  • management module EMM allows the following operation.
  • agent types for example Buyer, Seller
  • the ME engine module When the ME engine module operates in the client mode, it sends commands to the appropriate sub-modules.
  • the sent commands are: logging commands through which information is sent to the logging module LM and a Notification Command of an Up-to-date Configuration through which an up-to-date configuration is sent to the user interface module IUM.
  • the engine module ME waits for multiple commands when it operates in server mode.
  • these multiple commands comprise: - Agent commands, which refer to an agent life cycle and comprise the following commands: insert, INS-AG/ update, UPD-AG/ delete, KIL-AG / "execute matching", MACH / lock, LCK-AG/ unlock, ULCK-AG.
  • Agent commands refer to an agent life cycle and comprise the following commands: insert, INS-AG/ update, UPD-AG/ delete, KIL-AG / "execute matching", MACH / lock, LCK-AG/ unlock, ULCK-AG.
  • Agent commands which refer to an agent life cycle and comprise the following commands: insert, INS-AG/ update, UPD-AG/ delete, KIL-AG / "execute matching", MACH / lock, LCK-AG/ unlock, ULCK-AG.
  • - Feedback Command which notifies the engine module ME of the preference of a user as regards the occurrence and notification of a match.
  • - Structure Commands which refer to operations to perform on categories, sub-categories, matching items and features and they are: insert/update/delete; - Track Commands, through these commands some values of system parameters are queried, for example, the number of the agents present in the engine ME at that moment ;
  • Synchronization Commands through these commands the engine module ME is asked for the category structure, matching items, features etc.
  • the management module EMM can send this command to ask for the structure and modify it .
  • Figure 16 shows a diagram representing an example of the life cycle of an agent AGi managed by the engine module ME.
  • the life cycle shown in figure 16 includes the four states defined above, that is sleeping SLP, active ACT, locked LCK and dead state, DED.
  • the agent AGi is inserted by means of the "insert agent” command INS-AG which moves the agent to the sleeping state SLE.
  • the command "execute the matching" MACH the agent passes to the active state
  • the matching mode is defined synchronous, whereas the mode is defined asynchronous if this command MACH is given after a certain time interval from the command INS-AG.
  • the asynchronous mode incorporates a further configuration of the timing with which the command to execute the matching must be launched and of the modes with which the notification must occur.
  • NOTFYCATION step occurs refer to which of the two users of the two agents the notification of the occurred meeting must be sent to, where the closeness of the agents triggers the notification, the maximum number of matches that can be notified etc.
  • FIG 17 showing a window AG-TIMNG-CONF visible to the administrator to configure the timing of two types of agents AGT, made up of a buyer agent BUYR and a seller agent SELLR.
  • This window contains a check-box of each of the two names of the agents BUYR and SELLR which establishes that the agent must operate in synchronous or asynchronous mode. This check-box allows to establish if the respective agent must operate in a synchronous or asynchronous mode.
  • the asynchronous mode allows, through a text-box representing the length of the timer TMR, to fix an interval and when this time is up the matching is repeated.
  • the agent SELLR will operate in an asynchronous mode and it will execute the matching every hour.
  • a combo-box POLCY allows to determine the policy of the respective agent. For example, three types of agent policy can be determined. In the first case, “notify best” , the end of the agent life cycle is waited for and afterwards the notification of the best matches occurs. In the second case, “notify first”, only the best matches are notified and afterwards the agent passes to the dead state. In the third case, "notify all", every executed match is notified from time to time.
  • a combo-box NOTFYN it is decided how the match will be notified.
  • a text-box RNK the rank or minimum acceptable rank for a match, that is the minimum value of the rank under which the corresponding match is not notified.
  • the rank is a number that represents a satisfaction indicator resulting from the match.
  • a text-box MTCH and a text-box NTFY the maximum number of the matches which can be carried out for each matching request and the maximum number of matches that can be notified altogether are respectively fixed.
  • the window of figure 17 presents a finish button FINSH and a deletion button CANC.
  • the passage from the sleeping state SLE to the active state ACT can also be caused by an awakening command AWK arising from a matching search carried out by another agent. If a match has occurred, the agent Agi is moved back to the sleeping state SLE after the engine module ME has received a feedback command ENDMACH signalling that the match has occurred.
  • the agent AGi can pass to locked state LCK and from this to sleeping state SLP or to the dead one DED by means of locking commands LCK-AG, unlocking ULCK- AG, and agent "killing" KIL-AG.
  • Dead state DED can be reached starting from locked state LCK, from the active one ACT and from the sleeping one SLE, and also through killing command KIL-AG, beside by means of an expiry command EXP that is activated when the current date of the agent AGi equals the end date ED associated with the agent, described before with reference to figure 6.
  • an "external" state may be considered. This represents an agent implemented on a remote engine module, that is the module RME of figure 2. However, this agent which is not enabled for the match at observation time T is seen by the engine module ME as though it were in the sleeping state SLE or in the locked state LCK.
  • step INSER-DATA of figure 4 A situation, in which the configuration of the agents AGi has already been carried out according to procedures analogous to those described above (step INSER-DATA of figure 4) , will be taken into consideration.
  • one or more matching features MF are associated with each agent and these features contain a requested value R and an offered value O, as shown in figured 6.
  • Figure 18 shows the steps of the matching search in the form of a flow chart.
  • the method includes an INSER- AG step where all the agent AGi data are inserted.
  • the agent AGi is set to state SLP.
  • This step also comprises the sending of the command "insert agent" INS-AG to engine module ME.
  • the insertion of the agent AGi can be carried out by a user, a physical person, or by a program taking information from a source and inserting them in system 200 automatically.
  • the method continues with a step INV-MACH in which the execute matching command MACH is sent to the engine module ME of the system 200.
  • this command MACH is sent by the user interface module IUM which has converted a message coming from the user Ul who has requested, through his/her client system, the beginning of a matching search for the agent AGl associated with him/her.
  • the command MACH besides referring to the agent AGl, contains a field indicating the maximum number of matches K which are requested. It means that inside a number of agents, at most K agents are sought, so that they can "match" the agent AGl .
  • Step INV-MACH is followed by a selection step SELCT according to which those agents AGel eligible for the match with AGl are selected.
  • agents AGel are the agents for which the match with AGl does not correspond to a complete dissatisfaction neither of the user associated with AGl nor of any users associated with the corresponding Agel. After this selection the matching search continues only with reference to the selected eligible agents.
  • AG2 indicates a generically eligible agent associated with a generic user U2.
  • the engine module ME After selection step SELCT, the engine module ME carries out the first processing ELAB1.
  • the result Yj ⁇ ,j 2 of each of these comparison functions CF j! , j2 represents a first partial indication of the complementarity or affinity existing between the agent AGl and the agent AG2.
  • Each result Yj 2 ,ji of each comparison function CFj 2 ,ji represents a second partial indication of the complementarity or affinity existing between the agent AGl and the agent AG2.
  • the engine module ME executes a final processing ENDELAB on these results Yji,j 2 and Yj 2 ,ji, applying the function F(Yj l ⁇ j 2 #Yj2.ji) .
  • this final processing ENDELAB gives as a result a rank RK which represents a final indication of the affinity between agent AGl and the specific agent AG2.
  • the rank RK is calculated on the basis of the results Yji,j 2 and Yj 2 ,ji, taking other parameters into account also, that is a priori preference APP and/or user preference Upj associated with each matching feature MFi and MF j2 of AGl and AG2.
  • the rank RK can be a number between 0 and 1 inclusive, where 1 stands for a perfect affinity, that is a perfect match.
  • the first K that is the K agents AG2 having a higher rank, will be chosen during a choice step CHOS-AG.
  • a feedback step FED-BAK may occur in a step following the notification step NOTFY-US.
  • the user Ul sends to system 200 information representing the level of satisfaction of the user Ul resulting from the notified matches.
  • This message may contain the reasons why a specific match has been considered such as to satisfy the user and/or the reason why it has been considered more or less satisfying than another match.
  • the semantic blocks "very similar”, “similar”, “far”, “very far” are associated respectively with the value intervals of a comparison function CF 0.00 - 0.25; 0.25 - 0.50; 0.50 - 0.75 and 0.75 - 1.00.
  • the message which has to be notified can be produced automatically by scanning the values resulting from the comparison functions CF and by sending the user the semantic block in natural language associated with the specific interval.
  • the scan can occur in decreasing order according to the user preference Upj , where the user preferences Upj are associated with the requested values R the comparison functions are applied to.
  • the method ends with a final step ENDF. It is worth noting that thanks to the fact that both a requested value and an offered value are associated with each agent it is possible to apply a comparison function in a "crossed" way, for example, as described with reference to the steps ELAB1 and ELAB2, so that the level of satisfaction of both the agents involved in the match can be estimated.
  • the first agent Aga is defined according to the table 4.
  • the second agent Agb is defined as it is showed in table 5.
  • Figure 19 shows a window of EXPL-COD the administrator can use to carry out the explicit coding.
  • the vector values for each interest are reported: Show (SPECT), Legal (LEGL), Tourism (TURSM), Computer Science (INFOMT) , Commerce (COMM) , Economics (ECNOMY) , Politics (POLIT) , Music (MUSC) , Sport (SPRT) , Art (AR) , Travels (TRAV) for each sub-feature: Physical Effort (PH-EF) , "Sociality” (SOC) , "Cost” (CST) , "Culture” (CULTR) , "Playfulness” (GAM) .
  • the window EXPL-COD shows the OK button to confirm and the Cane button to delete.
  • the configuration of the matching items, the feature coding and the choice of the comparison functions are carried out by an administrator through management module EMM on the basis of an a priori knowledge in the field of human psychology and in that of psychology of interpersonal relations .
  • rank RK As described above with reference to final processing ENDELAB, according to the values of the calculated distances shown in table 7 rank RK can be calculated.
  • the rank RK is obtained subtracting the sum S of 8 addends divided by 8 from the number 1.
  • Each addend is obtained multiplying each calculated distance by the user preference UP and the a priori preference APP, set for each feature.
  • the rank value is of significance if compared with another rank. For example, let us take another agent Age associated with the user Alberto into consideration. Suppose Alberto has the same profile as Roberto except for the fact that he lives in Arezzo instead of Prato.
  • this information can be sent as feedback to the system (for example in the form of a scalar number between 0 and 1 inclusive where 1 stands for the maximum satisfaction and 0 for the maximum dissatisfaction) in order to be used by the algorithms of the particular embodiment .
  • the way in which the user's satisfaction is collected changes according to the implementation. For instance it can be collected in an implicit way, giving a score 0 if Daniela deletes Roberto's notification message, a score 0.7 if Daniela adds Roberto in her address book, 1.0 if Daniela sends Roberto a message.

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Abstract

L'invention concerne un procédé permettant d'extraire des informations disponibles au moyen d'au moins un ordinateur, ce procédé comprenant une étape qui consiste à rechercher un lien en fonction d'un but prédéfini, et au moyen d'un traitement électronique entre un premier agent (AG1) associé à un premier utilisateur (U1) et un second agent (AG2) associé à un second utilisateur (U2). Ce procédé consiste à associer (INSER-DATA), par stockage dans une mémoire, une première valeur requise (R-1) par le premier utilisateur (U1) et une seconde valeur offerte (O-2) par le second utilisateur (AG2) au premier agent (AG1) et au second agent (AG2) respectivement. Ce procédé est caractérisé en ce qu'il consiste en outre à associer (INSER-DATA), par stockage dans une mémoire, une première valeur offerte (O-1) par le premier utilisateur (U1) et une seconde valeur requise (R-2) par le second utilisateur au premier agent (AG1) et au second agent (AG2) respectivement.
EP01919771A 2001-03-29 2001-03-29 Procede et systeme d'extraction d'informations Ceased EP1346297A1 (fr)

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US5794210A (en) * 1995-12-11 1998-08-11 Cybergold, Inc. Attention brokerage
AU1836297A (en) * 1996-01-17 1997-08-11 Personal Agents, Inc. Intelligent agents for electronic commerce
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