Flexible queries in relational databases—the example of the division operator
Selected papers from the international workshop on Uncertainty in databases and deductive systems
Logical models in information retrieval: introduction and overview
Information Processing and Management: an International Journal
Extended Boolean information retrieval
Communications of the ACM
Journal of the American Society for Information Science and Technology
Vagueness and uncertainty in information retrieval: how can fuzzy sets help?
Proceedings of the 2006 international workshop on Research issues in digital libraries
Personalized information retrieval system in the framework of fuzzy logic
Expert Systems with Applications: An International Journal
On a Parameterized Antidivision Operator for Database Flexible Querying
DEXA '08 Proceedings of the 19th international conference on Database and Expert Systems Applications
Threshold values and Boolean retrieval systems
Information Processing and Management: an International Journal
A model for information retrieval based on possibilistic networks
SPIRE'05 Proceedings of the 12th international conference on String Processing and Information Retrieval
Strict and tolerant antidivision queries with ordinal layered preferences
International Journal of Approximate Reasoning
Implication in information retrieval systems
RIAO '10 Adaptivity, Personalization and Fusion of Heterogeneous Information
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This paper investigates the use of fuzzy logic mechanisms coming from the database community, namely graded inclusions, to model the information retrieval process. 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.