Data mining: concepts and techniques
Data mining: concepts and techniques
Data Mining: An Overview from a Database Perspective
IEEE Transactions on Knowledge and Data Engineering
Mining Multiple-Level Association Rules in Large Databases
IEEE Transactions on Knowledge and Data Engineering
Knowledge Discovery in Databases: An Attribute-Oriented Approach
VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
Discovery of Multiple-Level Association Rules from Large Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Using information content to evaluate semantic similarity in a taxonomy
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
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This paper presents an approach to produce generalization candidates for a concept hierarchy without the necessity of being an expert in the domain to be generalized and its application to the summarization of large descriptive data sets. Through the use of ontologies, a set of terms can be automatically generalized into the next abstract level in a concept hierarchy. A new approach for the extraction of minimally abstract generalizations of provided terms from ontologies, and for unsupervised construction of a fuzzy concept hierarchy for attribute-oriented purposes will be presented. The algorithm presented is a proof-of-concept type and it will be followed by future research.