Axiomatic Term-Based Personalized Query Expansion Using Bookmarking System

Philippe Mulhem (1, 2) , Nawal Ould Amer (1, 3, 2) , Mathias Géry (3)

1 LIG - Laboratoire d'Informatique de Grenoble
2 MRIM - Modélisation et Recherche d’Information Multimédia [Grenoble]
3 LHC - Laboratoire Hubert Curien

This paper tackles the problem of pinpointing relevant information in a social network for Personalized Information Retrieval (PIR). We start from the premise that user profiles must be filtered so that they outperform non profile based queries. The formal Profile Query Expansion Constraint is then defined. We fix a specific integration of profile and a probabilistic matching framework that fits into the constraint defined. Experiments are conducted on the Bibson-omy corpus. Our findings show that even simple profile adaptation using query is effective for Personalized Information Retrieval.

Keywords: social network; probabilistic retrieval; profile selection; axiomatic IR

Domains: Computer Science [cs]; Information Retrieval [cs.IR]

Philippe Mulhem, Nawal Ould Amer, Mathias Géry. Axiomatic Term-Based Personalized Query Expansion Using Bookmarking System. Database and Expert Systems Applications - 27th International Conference, DEXA 2016, Sep 2016, Porto, Portugal. pp.235 - 243, ⟨10.1007/978-3-319-44406-2_17⟩. ⟨ujm-01377069⟩