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

Zhan Gui, Ernesto Damiani, Marcello Leida, Marco Viviani

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

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.

Original languageBritish English
Title of host publicationKnowledge-Based Intelligent Information and Engineering Systems - 9th International Conference, KES 2005, Proceedings
Pages112-118
Number of pages7
StatePublished - 2005
Event9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005 - Melbourne, Australia
Duration: 14 Sep 200516 Sep 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3681 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005
Country/TerritoryAustralia
CityMelbourne
Period14/09/0516/09/05

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