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.
Cui, Z., Damiani, E., Leida, M., Viviani, M. (2005). OntoExtractor: A fuzzy-based approach in clustering semi-structured data sources and metadata generation. In KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT 1, PROCEEDINGS (pp.112-118) [10.1007/11552413_17].
OntoExtractor: A fuzzy-based approach in clustering semi-structured data sources and metadata generation
Damiani, E;Viviani, M.
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.
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