MINING THE WEB FOR LEARNING THE ONTOLOGY

Bassam M. Aoun, Marie Khair

Abstract

The Semantic Web is a network of information linked up in such a way as to be easily processed by machines, on a global scale. To reach semantic web, current web resources should be automatically translated into semantic web resources. This is usually performed through semantic web mining, which aims at combining the two fast-developing research areas, the Semantic Web and Web Mining. A major step to be performed is the ontology-learning phase, where rules are mined from unstructured text and used later on to fill the ontology. Making sure that all rules are found and no additional and inaccurate rules are inserted, remains a critical issue since it constitutes the basis for building the semantic web. The mostly used algorithm for this task is the Apriori algorithm, which is inherited from classical data mining. However, due to the nature of the semantic web, some important rules can be dropped. This paper presents an enhanced version of the Apriori algorithm, En_Apriori, which uses the Apriori algorithm in combination with the maximal association and the X2 test to generate association rules from web/textual documents. This provides a major refinement to the classical ontology learning approach.

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Paper Citation


in Harvard Style

M. Aoun B. and Khair M. (2007). MINING THE WEB FOR LEARNING THE ONTOLOGY . In Proceedings of the Second International Conference on Software and Data Technologies - Volume 3: ICSOFT, ISBN 978-989-8111-07-4, pages 189-192. DOI: 10.5220/0001348101890192


in Bibtex Style

@conference{icsoft07,
author={Bassam M. Aoun and Marie Khair},
title={MINING THE WEB FOR LEARNING THE ONTOLOGY},
booktitle={Proceedings of the Second International Conference on Software and Data Technologies - Volume 3: ICSOFT,},
year={2007},
pages={189-192},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001348101890192},
isbn={978-989-8111-07-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Software and Data Technologies - Volume 3: ICSOFT,
TI - MINING THE WEB FOR LEARNING THE ONTOLOGY
SN - 978-989-8111-07-4
AU - M. Aoun B.
AU - Khair M.
PY - 2007
SP - 189
EP - 192
DO - 10.5220/0001348101890192