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. © Springer-Verlag Berlin Heidelberg 2005.
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CITATION STYLE
Nakayama, K., Hara, T., & Nishio, S. (2005). A web mining method based on personal ontology for semi-structured RDF. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3807 LNCS, pp. 227–234). https://doi.org/10.1007/11581116_24
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