A profile-based aggregation model in a peer-to-peer information retrieval system

Rim Mghirbi (1, 2, 3, 4) , Khedija Arour (3) , Yahya Slimani (3) , Bruno Defude (5, 1, 2, 4)

1 TSP - INF - Département Informatique
2 SAMOVAR - Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux
3 FST - Département d'informatique
4 CNRS - Centre National de la Recherche Scientifique
5 ACMES-SAMOVAR - Architecture, Cloud continuum, formal Models, artificial intElligence and Services in distributed computing

Measuring effectiveness of Distributed Information Retrieval (DIR) is essential for research and development and for monitoring search quality in dynamic environment. Numerous works have been done to propose new search models in the context of peer-to-peer information retrieval systems (P2P-IR). In this article, we are considering another problem, which is the global ranking of a set of results' lists coming from a large set of IR systems. In this article we define a new method for automatic aggregation of results which mixes these categories by allowing each peer to construct knowledge about other peers' relevance model using a learning method (Formal Concept Analysis). The idea is that each peer constructs relationships between past queries, returned documents and contributed peers

Mots clés: IR; Information retrieval; P2P systems; Rank aggregation; User profiles

Domaines: Calcul parallèle, distribué et partagé [cs.DC]

Rim Mghirbi, Khedija Arour, Yahya Slimani, Bruno Defude. A profile-based aggregation model in a peer-to-peer information retrieval system. Globe 2010 : 3rd International Conference on Data Management in Grid and P2P Systems, Sep 2010, Bilbao, Spain. pp.148 - 159, ⟨10.1007/978-3-642-15108-8_13⟩. ⟨hal-01333421⟩