IRIT-QFR: IRIT Query Feature Resource

Serge Molina (1) , Josiane Mothe (1, 2) , Dorian Roques (3) , Ludovic Tanguy (4) , Md Zia Ullah (1)

1 IRIT-SIG - Systèmes d’Informations Généralisées
2 UT2J - Université Toulouse - Jean Jaurès
3 IRIT-REVA - Real Expression Artificial Life
4 CLLE-LTC - Cognition, Langues, Langage, Ergonomie

In this paper, we present a resource that consists of query features associated with TREC adhoc collections. We developed two types of query features: linguistics features that can be calculated from the query itself, prior to any search although some are collection-dependent and post-retrieval features that imply the query has been evaluated over the target collection. This paper presents the two types of features that we have estimated as well as their variants, and the resource produced. The total number of features with their variants that we have estimated is 258 where the number of pre-retrieval and post-retrieval features are 81 and 171, respectively. We also present the first analysis of this data that shows that some features are more relevant than others in IR applications. Finally, we present a few applications in which these resources could be used although the idea of making them available is to foster new usages for IR.

Mots clés: Query features; IR resource; Information retrieval; Information systems; Query feature analysis

Domaines: Théorie de l'information [cs.IT]; Recherche d'information [cs.IR]

Serge Molina, Josiane Mothe, Dorian Roques, Ludovic Tanguy, Md Zia Ullah. IRIT-QFR: IRIT Query Feature Resource. International Conference of the Cross-Language Evaluation Forum for European Languages (CLEF 2017), Sep 2017, Dublin, Ireland. pp.69-81. ⟨hal-01913678⟩