Information retrieval: data structures and algorithms
Information retrieval: data structures and algorithms
Information filtering and information retrieval: two sides of the same coin?
Communications of the ACM - Special issue on information filtering
Knowledge compilation and theory approximation
Journal of the ACM (JACM)
Capabilities-based query rewriting in mediator systems
DIS '96 Proceedings of the fourth international conference on on Parallel and distributed information systems
Ontology-based metadata generation from semi-structured information
Proceedings of the 1st international conference on Knowledge capture
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Boolean Query Mapping Across Heterogeneous Information Sources
IEEE Transactions on Knowledge and Data Engineering
Description Logics for Information Integration
Computational Logic: Logic Programming and Beyond, Essays in Honour of Robert A. Kowalski, Part II
Approximate query mapping: Accounting for translation closeness
The VLDB Journal — The International Journal on Very Large Data Bases
Using a semantic network for information extraction
Natural Language Engineering
Word-sense disambiguation using statistical models of Roget's categories trained on large corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
A framework for a fuzzy matching between multiple domain ontologies
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part I
Mapping fuzzy concepts between fuzzy ontologies
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
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Facing the increasing amount of information available on the World Wide Web, intelligent techniques for content-based information filtering gain more and more importance. Conventional approaches using keyword- or text-based retrieval methods have been developed that perform reasonably well. However, these approaches have problems with ambiguous and imprecise information. The semantic web that aims at supplementing information sources with a formal specification of its meaning using ontologies can potentially help to overcome this problem. At the moment, however, the semantic web still suffers from its own problems in terms of heterogeneous ontologies and the need to relate them to each other. In this paper, we argue that we can overcome this problem by using shared vocabularies, a standardized language for encoding ontology that supports basic terminological reasoning (in this case DAML+OIL) and techniques from approximate reasoning. We introduce the approach on an informal level using didactic example and give a formal characterization of the method that include correctness proofs for the problem of information filtering.