A web mining method based on personal ontology for semi-structured RDF

Authors:
Kotaro Nakayama;Takahiro Hara;Shojiro Nishio
Affiliations:
Dept. of Multimedia Eng., Graduate School of Information Science and Technology, Osaka University, Osaka, Japan;Dept. of Multimedia Eng., Graduate School of Information Science and Technology, Osaka University, Osaka, Japan;Dept. of Multimedia Eng., Graduate School of Information Science and Technology, Osaka University, Osaka, Japan
Venue:
WISE'05 Proceedings of the 2005 international conference on Web Information Systems Engineering
Year:
2005

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Abstract

In order to improve Semantic Web Mining, as a precondition, there have to be enough data that are “well”-structured by linking to other web resources. However, Semantic Web data in real world, such as RSS and Dublin Core, are just semi-structured documents in most cases, because the main part of the content is still mixed with text data. In this paper, we propose a new Web Mining method based on Personal Ontology, a concept dictionary in the local machine personalized for each user which maps to web resource. Our approach accomplished Semantic Web Mining for semi-structured data such as RSS.