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Une approche adaptative pour la recherche d'information sur le Web

Cédric Pruski 1, 2, 3
2 GEMO - Integration of data and knowledge distributed over the web
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623
Abstract : The advent of the Web in the early 90s has deeply upset our society. This new media has rapidly become the greatest database in the world. Moreover, the ever increasing popularity of the Web engendered a huge dynamics with respect to Web data. Actually, by virtue of knowledge evolution, data is permanently added, deleted or updated from the Web which raises important issues regarding Web information retrieval. Existing Web search engines are neither able to take knowledge evolution into account when users submit their queries nor able to understand users' needs in order to return the most relevant information to users. The Semantic Web, proposed in 2001 and which aims at giving a sense to Web data in order to make it machine understandable, helps to improve Web search but knowledge evolution is still problematic. In this work, we address the problem of taking knowledge evolution for improving Web search in the sense of relevance of the returned results. The advocated solution is based on the use of ontologies, cornerstone of the Semantic Web, for representing both the domain targeted by the query and the profile of the user who submit the query. Ontologies are considered as knowledge that is evolving over time. In consequence, the ontology evolution problem has to be tackled as regards the evolution of the targeted domain but also with respect to the evolution of users' profile. First of all, we introduce a new paradigm: adaptive ontology as well as a process for making adaptive ontologies smoothly follow evolution of a domain. The so-defined model relies on the adaptation of ideas developed in the field of psychology and biology to the knowledge engineering field. Then, we propose an approach exploiting adaptive ontologies for improving Web information retrieval. To this end, we first introduce data structures, WPGraphs and W3Graphs, for representing Web data. We then introduce the ASK query language tailored for the extraction of relevant information from these structures. We also propose a set of query enrichment rules based on the exploitation of ontological elements as well as adaptive ontologies characteristics of the ontology representing the domain targeted by the query and the one representing the view of the user on the domain. Lastly, we introduce a tool for managing adaptive ontologies and for searching relevant information on the Web as well as an experimental validation of the introduced concepts. We based our validation on the definition of a realistic case study devoted to the retrieval of scientific articles published at the International World Wide Web series of conference.
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Submitted on : Wednesday, November 18, 2009 - 9:24:44 AM
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Cédric Pruski. Une approche adaptative pour la recherche d'information sur le Web. Interface homme-machine [cs.HC]. Université Paris Sud - Paris XI; université du Luxembourg, 2009. Français. ⟨tel-00433071⟩

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