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Implication-based and cardinality-based inclusions in information retrieval

Patrick Bosc 1 Laurent Ughetto 2 Olivier Pivert 1 Vincent Claveau 2 
1 PILGRIM - Gradedness, Imprecision, and Mediation in Database Management Systems
2 TEXMEX - Multimedia content-based indexing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : This paper investigates the use of fuzzy logic mechanisms coming from the database community, namely graded inclusions, to model the information retrieval process. Two kinds of graded inclusions are considered. In this framework, documents and queries are represented by fuzzy sets, which are paired with operations like fuzzy implications and T-norms. Through different experiments, it is shown that only some among the wide range of fuzzy operations are relevant for information retrieval. When appropriate settings are chosen, it is possible to mimic classical systems, thus yielding results rivaling those of state-of-the-art systems. These positive results validate the proposed approach, while negative ones give some insights on the properties needed by such a model. Moreover, this paper shows the added-value of this graded inclusion-based model, which gives new and theoretically grounded ways for a user to easily weight his query terms, to include negative information in his queries, or to expand them with related terms.
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Submitted on : Friday, July 12, 2013 - 12:31:02 PM
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Patrick Bosc, Laurent Ughetto, Olivier Pivert, Vincent Claveau. Implication-based and cardinality-based inclusions in information retrieval. FUZZ-IEEE - IEEE International Conference on Fuzzy Systems, Aug 2009, Jeju Island, South Korea. pp.2088 - 2093, ⟨10.1109/FUZZY.2009.5277249⟩. ⟨hal-00843889⟩



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