Modelling information retrieval agents with belief revision
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Some simple effective approximations to the 2-Poisson model for probabilistic weighted retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Pivoted document length normalization
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Using a belief revision operator for document ranking in extended Boolean models
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
A vector space model for automatic indexing
Communications of the ACM
Information Retrieval: Uncertainty and Logics: Advanced Models for the Representation and Retrieval of Information
Exploiting the Similarity of Non-Matching Terms at RetrievalTime
Information Retrieval
Journal of the American Society for Information Science and Technology - Mathematical, logical, and formal methods in information retrieval
Implementing Document Ranking within a Logical Framework
SPIRE '00 Proceedings of the Seventh International Symposium on String Processing Information Retrieval (SPIRE'00)
Bayesian extension to the language model for ad hoc information retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Language Modeling for Information Retrieval
Language Modeling for Information Retrieval
Belief revision for adaptive information retrieval
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Propositional logic representations for documents and queries: a large-scale evaluation
ECIR'03 Proceedings of the 25th European conference on IR research
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An unsolved problem in logic-based information retrieval is how to obtain automatically logical representations for documents and queries. This problem limits the impact of logical models for information retrieval because their full expressive power cannot be harnessed. In this paper we propose a method for producing logical document representations which goes further than other simplistic "bag-of-words" approaches. The suggested procedure adopts popular information retrieval heuristics, such as document length corrections and global term distribution. This work includes a report of several experiments applying partial document representations in the context of a propositional model of information retrieval. The benefits of this expressive framework, powered by the new logical indexing approach, become apparent in the evaluation.