An outline of a general model for information retrieval systems
SIGIR '88 Proceedings of the 11th annual international ACM SIGIR conference on Research and development in information retrieval
Epistemic entrenchment and possibilistic logic
Artificial Intelligence
About retrieval models and logic
The Computer Journal - Special issue on information retrieval
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Communications of the ACM - Special issue on information filtering
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Context-sensitive learning methods for text categorization
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On the role of logic in information retrieval
Information Processing and Management: an International Journal
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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
Aboutness from a commonsense perspective
Journal of the American Society for Information Science
The score-distributional threshold optimization for adaptive binary classification tasks
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Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
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Conceptual Spaces: The Geometry of Thought
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Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
The Psychology of Human-Computer Interaction
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Comparing the Performance of Adaptive Filtering and Ranked Output Systems
Information Retrieval
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ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
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ICSC '99 Proceedings of the 5th International Computer Science Conference on Internet Applications
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Journal of the American Society for Information Science and Technology - Mathematical, logical, and formal methods in information retrieval
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ICTAI '96 Proceedings of the 8th International Conference on Tools with Artificial Intelligence
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WI '03 Proceedings of the 2003 IEEE/WIC International Conference on Web Intelligence
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TARK '88 Proceedings of the 2nd conference on Theoretical aspects of reasoning about knowledge
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IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
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ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part I
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In an adaptive information retrieval (IR) setting, the information seekers' beliefs about which terms are relevant or nonrelevant will naturally fluctuate. This article investigates how the theory of belief revision can be used to model adaptive IR. More specifically, belief revision logic provides a rich representation scheme to formalize retrieval contexts so as to disambiguate vague user queries. In addition, belief revision theory underpins the development of an effective mechanism to revise user profiles in accordance with information seekers' changing information needs. It is argued that information retrieval contexts can be extracted by means of the information-flow text mining method so as to realize a highly autonomous adaptive IR system. The extra bonus of a belief-based IR model is that its retrieval behavior is more predictable and explanatory. Our initial experiments show that the belief-based adaptive IR system is as effective as a classical adaptive IR system. To our best knowledge, this is the first successful implementation and evaluation of a logic-based adaptive IR model which can efficiently process large IR collections.