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Abstract

The main objective of an information retrieval system is to provide relevant information in response to the user's query. On the one part, the relevance of a response concerns its exactness compared with the user's query. On the other part, it concerns its correspondence with the user's knowledge level and his preferences. One of the major contribution in this area of personalization of the system's response is by taking into consideration each user's specifity. We propose the use of explicit user model where the system's solution will be determined by the knowledge of the user. The user's activities are recorded as documents. The method we adopt for information retrieval combines query by criteria and information analysis. We have also proposed architecture for cooperative information retrieval. This architecture allows 2 users to share their experience in the process of information retrieval and for the interpretation of the system's result, on distant machines. The proposals were implemented in 2 systems: STREEMS and METIORE. STREEMS manages information on trees while METIORE manages information on bibliographic references

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Footnote

Übers. d. Titels: Modelling the user and co-operative searching in information retrieval systems

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Abstract

Our hypothesis is that when a user employs an IRS, he or she has an objective to achieve. This objective concerns the user's information need. In order to achieve this objective, the user generally does some activities using the IRS. The IRS proposes to the user solutions in response to the queries formulated by the user. The main task of an IRS is to provide the user with solutions that are relevant to his information need. This is termed personalization of information. The main axis of our study is how to personalize the system's response according to the user's objective. We propose the use of a user model for personalizing the system's response. In our approach, the user model defines what to represent for each user. The activities of the user during the use of an IRS are recorded based on the user model. The analysis and synthesis of these activities are used to provide the user with more relevant solutions according to his objective. Three different applications have been developed to validate our approach of personalizing the system's response and based on an architecture that we defined for a cooperative information retrieval. The three applications are METIORE_STREEMS, METIORE_LORIA and METlORE_REVUES. METIORE_STREEMS is an IRS for managing multimedia information on trees authorized for reforestation by the European Union (EU). The project was sponsored under the EU project LEONARDO. The second application, METIORE_LORIA is used for managing the publications of the computer science laboratory research center, LORIA, Nancy, France. The third application METIORE_REVUES is used for the access and analysis of a journal called Relations Publics Information