Ontology-based automatic classification for Web pages: Design, implementation and evaluation
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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WISE 2002 - Proceedings of the 3rd International Conference on Web Information Systems Engineering. ed. / Wee Keong Ng; Tok Wang Ling; Angela Goh; Umeshwar Dayal; Elisa Bertino. IEEE - Institute of Electrical and Electronics Engineers Inc., 2002. p. 182-191 1181655.
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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TY - CHAP
T1 - Ontology-based automatic classification for Web pages
T2 - 3rd International Conference on Web Information Systems Engineering - WISE 2002
AU - Prabowo, R.
AU - Jackson, M.
AU - Burden, P.
AU - Knoell, H. D.
N1 - Conference code: 3
PY - 2002
Y1 - 2002
N2 - In recent years, we have witnessed continual growth in the use of ontologies in order to provide a mechanism to enable machine reasoning. This paper describes an automatic classifier, which focuses on the use of ontologies for classifying Web pages with respect to Dewey Decimal Classification (DDC) and Library of Congress Classification (LCC) schemes. Firstly, we explain how these ontologies can be built in a modular fashion, and mapped into DDC and LCC. Secondly, we propose the formal definition of a DDC-LCC and an ontology-classification-scheme mapping. Thirdly, we explain the way the classifier uses these ontologies to assist classification. Finally, an experiment in which the accuracy of the classifier was evaluated is presented. The experiment shows that our approach results an improved classification in terms of accuracy. This improvement, however, comes at a cost in a low coverage ratio due to incompleteness of the ontologies used.
AB - In recent years, we have witnessed continual growth in the use of ontologies in order to provide a mechanism to enable machine reasoning. This paper describes an automatic classifier, which focuses on the use of ontologies for classifying Web pages with respect to Dewey Decimal Classification (DDC) and Library of Congress Classification (LCC) schemes. Firstly, we explain how these ontologies can be built in a modular fashion, and mapped into DDC and LCC. Secondly, we propose the formal definition of a DDC-LCC and an ontology-classification-scheme mapping. Thirdly, we explain the way the classifier uses these ontologies to assist classification. Finally, an experiment in which the accuracy of the classifier was evaluated is presented. The experiment shows that our approach results an improved classification in terms of accuracy. This improvement, however, comes at a cost in a low coverage ratio due to incompleteness of the ontologies used.
KW - Informatics
UR - http://www.scopus.com/inward/record.url?scp=84961208893&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/40db05e1-cfef-37df-b6ee-5f28b061611f/
U2 - 10.1109/WISE.2002.1181655
DO - 10.1109/WISE.2002.1181655
M3 - Article in conference proceedings
AN - SCOPUS:84961208893
SN - 0769517668
SN - 9780769517667
SP - 182
EP - 191
BT - WISE 2002 - Proceedings of the 3rd International Conference on Web Information Systems Engineering
A2 - Ng, Wee Keong
A2 - Ling, Tok Wang
A2 - Goh, Angela
A2 - Dayal, Umeshwar
A2 - Bertino, Elisa
PB - IEEE - Institute of Electrical and Electronics Engineers Inc.
Y2 - 12 December 2002 through 14 December 2002
ER -