This paper describes a theoretical approach on data mining, information classifying and a global overview of our OntoExtractor application, concerning the analysis of incoming data flow and generate metadata structures. In order to help the user to classify a big and varied group of data, our proposal is to use fuzzy-based techniques to compare and classify the data. Before comparing the elements, the incoming flow of information has to be converted into a common structured format like XML. With those structured documents now we can compare and cluster the various data and generate a metadata structure about this data repository.

OntoExtractor : A fuzzy-based approach in clustering semi-structured data sources and metadata generation / Zhan Cui, Ernesto Damiani, Marcello Leida, Marco Viviani - In: Knowledge-based intelligent information and engineering systems : 9th international conference, KES 2005, Melbourne, Australia, september 14-16, 2005 : proceedings : part 1 / R. Khosla, R.J. Howlett, L.C. Jain. - Berlin : Springer, 2005. - ISBN 3540288945. - pp. 112-118 (( Intervento presentato al 9. convegno KES 2005 : 9th International Conference on Knowledge-Based & Intelligent Information & Engineering Systems tenutosi a Melbourne nel 2005.

OntoExtractor : A fuzzy-based approach in clustering semi-structured data sources and metadata generation

Ernesto Damiani;Marcello Leida;Marco Viviani
2005

Abstract

This paper describes a theoretical approach on data mining, information classifying and a global overview of our OntoExtractor application, concerning the analysis of incoming data flow and generate metadata structures. In order to help the user to classify a big and varied group of data, our proposal is to use fuzzy-based techniques to compare and classify the data. Before comparing the elements, the incoming flow of information has to be converted into a common structured format like XML. With those structured documents now we can compare and cluster the various data and generate a metadata structure about this data repository.
Settore INF/01 - Informatica
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/12838
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