Agents that reduce work and information overload
Communications of the ACM
Query expansion using lexical-semantic relations
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Information Processing and Management: an International Journal
OntoSeek: Content-Based Access to the Web
IEEE Intelligent Systems
Effective Reformulation of Boolean Queries with Concept Lattices
FQAS '98 Proceedings of the Third International Conference on Flexible Query Answering Systems
Incorporating user search behavior into relevance feedback
Journal of the American Society for Information Science and Technology
Information-Need Driven Query Refinement
WI '03 Proceedings of the 2003 IEEE/WIC International Conference on Web Intelligence
IEEE Intelligent Systems
Improving web-query processing through semantic knowledge
Data & Knowledge Engineering
Personalized Ontology-Based Query Expansion
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Ontology-based interpretation of keywords for semantic search
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
VQS – an ontology-based query system for the SemanticLIFE digital memory project
OTM'06 Proceedings of the 2006 international conference on On the Move to Meaningful Internet Systems: AWeSOMe, CAMS, COMINF, IS, KSinBIT, MIOS-CIAO, MONET - Volume Part II
Using semantic knowledge to improve web query processing
NLDB'06 Proceedings of the 11th international conference on Applications of Natural Language to Information Systems
International Journal of Knowledge-based and Intelligent Engineering Systems - Selected papers of KES2012-Part 1 of 2
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In this paper we present a comprehensive approach for the refinement of ontology-based queries, which is based on incrementally (step-by-step) and interactively tailoring a query to the current information needs of a user, whereas these needs are implicitly and on-line elicited by analysing the user's behaviour during the searching process. The gap between a user's need and his query is quantified by measuring several types of query ambiguities. Consequently, in the refinement process a user is provided with a ranked list of refinements, which leads to a decrease of some of these ambiguities. Moreover, by exploiting the ontology background, the approach supports finding "similar" results that can help a user to satisfy his information need.