Current applications of data mining techniques highlight the need for flexible knowledge discovery systems, capable of supporting the user in specifying and re.ning mining objectives, combining multiple strategies, and de.ning the quality of the extracted knowledge. A key issue is the de.nition of Knowledge Discovery Support Environment, i.e., a query system capable of obtaining, maintaining, representing and using high level knowledge in a uni.ed framework. This comprises representation and manipulation of domain knowledge, extraction and manipulation of new knowledge and their combination.

LDLMine : Integrating Data Mining with Intelligent Query Answering

Giannotti F;Manco G
2002

Abstract

Current applications of data mining techniques highlight the need for flexible knowledge discovery systems, capable of supporting the user in specifying and re.ning mining objectives, combining multiple strategies, and de.ning the quality of the extracted knowledge. A key issue is the de.nition of Knowledge Discovery Support Environment, i.e., a query system capable of obtaining, maintaining, representing and using high level knowledge in a uni.ed framework. This comprises representation and manipulation of domain knowledge, extraction and manipulation of new knowledge and their combination.
2002
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
3-540-44190-5
Association Rule
Mining Algorithm
Mining Aggregate
High Level Knowledge
Mining Scheme
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/235841
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