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).
Citazione: | 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). |
Tipo: | slide + paper |
Carattere della pubblicazione: | Scientifica |
Presenza di un coautore afferente ad Istituzioni straniere: | Si |
Titolo: | OntoExtractor: A Fuzzy-Based Approach in Clustering Semi-structured Data Sources and Metadata Generation |
Autori: | Cui, Z; Damiani, E; Leida, M; Viviani, M |
Autori: | |
Data di pubblicazione: | 2005 |
Lingua: | English |
Nome del convegno: | International Conference on Knowledge-Based Intelligent Information and Engineering Systems SEP 14-16 |
ISBN: | 978-3-540-28894-7 |
Serie: | LECTURE NOTES IN ARTIFICIAL INTELLIGENCE |
Appare nelle tipologie: | 02 - Intervento a convegno |