ARIA

Association Francophone de Recherche d’Information (RI) et Applications

Actes de CORIA 2008
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Auteurs

Quoc Dinh Truong, Taoufiq Dkaki, Josiane Mothe, Pierre-Jean Charrel

Résumé

None

Abstract

GVC is a new information retrieval model that is based on Graph Vertices Comparison (GVC). It implements a new similarity measure to compare documents and users’ queries based on graph matching. In this model, graphs are composed of two types of nodes. Documents, queries and indexing terms are viewed as vertices of this bipartite graph where each edge goes from a document or a query ufirst type of nodes- to an indexing term u second type of nodes-. Edges reflect the relationship that exists between documents or queries on the one hand and indexing terms on the other hand; they are set according to the tf.idf principal. Our method implements similarity propagation over graph edges using an iterative process. We evaluate the model using 4 different collections (TREC 2004 Novelty Track, CISI, Cranfield and Medline). We show that considering precision at 5 documents, GVC outperforms Okapi model from 9% to 62%, depending on the collections.

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A Propos

ARIA (Association Francophone de Recherche d’Information (RI) et Applications) est une société savante, association loi 1901, ayant pour but de promouvoir le savoir et les connaissances du domaine de la Recherche d’Information (RI) et des divers domaines scientifiques en jeu dans la conception, la réalisation et l’évaluation des systèmes de Recherche d’Information.