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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Bouchon-Meunier, B., Rifqi, M., Bothorel, S.: Towards general measures of comparison of objects. Fuzzy Sets and Systems 84, 143–153 (1996)
Ceravolo, P.: Extracting Role Hierarchies from Authentication Data Flows. Computer Systems Science & Engineering Journal (IJCSSE) 19(3), 121–127 (2004)
Ceravolo, P., Nocerino, M.C., Viviani, M.: Knowledge Extraction from Semistructured Data Based on Fuzzy Techniques. In: Knowledge-Based Intelligent Information and Engineering Systems, Proceedings of the 8th International Conference, KES 2004, Part III, pp. 328–334 (2004)
Damiani, E., Nocerino, M.C., Viviani, M.: Knowledge Extraction from an XML Data Flow: Building a Taxonomy based on Clustering Technique, Current Issues in Data and Knowledge Engineering. In: Proceedings of EUROFUSE 2004: 8th Meeting of the EURO Working Group on Fuzzy Sets, pp. 133–142 (2004)
Leida, M.: Structural information extraction techniques from semi-structured data flows, coming from differents data sources, Università degli Studi di Milano, DTI – Note del Polo – Research, No. 70 (2005)
RDF W3C Recommendation http://www.w3.org/TR/rdf-primer/
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Cui, Z., Damiani, E., Leida, M., Viviani, M. (2005). OntoExtractor: A Fuzzy-Based Approach in Clustering Semi-structured Data Sources and Metadata Generation. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552413_17
Download citation
DOI: https://doi.org/10.1007/11552413_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28894-7
Online ISBN: 978-3-540-31983-2
eBook Packages: Computer ScienceComputer Science (R0)