SAINTETIQ: a fuzzy set-based approach to database summarization
Fuzzy Sets and Systems - Data bases and approximate reasoning
Using a web-based categorization approach to generate thematic metadata from texts
ACM Transactions on Asian Language Information Processing (TALIP)
Querying a summary of database
Journal of Intelligent Information Systems
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Fuzzy Sets and Systems
Data mining by attribute generalization with fuzzy hierarchies in fuzzy databases
Fuzzy Sets and Systems
Fuzzy induction in dynamic user profiling for information filtering
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Fuzzy sets in database and information systems: Status and opportunities
Fuzzy Sets and Systems
Automatic taxonomy generation: issues and possibilities
IFSA'03 Proceedings of the 10th international fuzzy systems association World Congress conference on Fuzzy sets and systems
Ontological summaries through hierarchical clustering
ISMIS'08 Proceedings of the 17th international conference on Foundations of intelligent systems
A framework for use of imprecise categorization in developing intelligent systems
IEEE Transactions on Fuzzy Systems
International Journal of Approximate Reasoning
Negotiation as creative social interaction using concept hierarchies
IPMU'10 Proceedings of the Computational intelligence for knowledge-based systems design, and 13th international conference on Information processing and management of uncertainty
From data to global generalized knowledge
Decision Support Systems
Querying e-catalogs using content summaries
ODBASE'06/OTM'06 Proceedings of the 2006 Confederated international conference on On the Move to Meaningful Internet Systems: CoopIS, DOA, GADA, and ODBASE - Volume Part I
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advences in computational intelligence - Volume Part II
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Summary discovery is one of the major components of knowledge discovery in databases, which provides the user with comprehensive information for grasping the essence from a large amount of information in a database. We propose an interactive top down summary discovery process which utilizes fuzzy ISA hierarchies as domain knowledge. We define a generalized tuple as a representational form of a database summary including fuzzy concepts. By virtue of fuzzy ISA hierarchies where fuzzy ISA relationships common in actual domains are naturally expressed, the discovery process comes up with more accurate database summaries. We also present an informativeness measure for distinguishing generalized tuples that delivers much information to users, based on C. Shannon's (1948) information theory