Abstract
We propose ways to discover semantic relationships among Web pages, andits applications in Web search, such as detailed-of, simplified-of, similar-topic-of, different-topic-of relationships.
In order to discover those semantic relationships, we propose two methods: One is based on ‘topic structures’ of Web pages. A topic structure of a Web page is computed by the combination of the term-appearancedensity-distribution of each page and the term co-occurrence ratio for all the term-pairs in all retrieved pages. The other is based on the ‘inclusion’ relationships among feature vectors of Web pages. We describe both of their algorithms and their evaluations.
The original version of this chapter was revised: The copyright line was incorrect. This has been corrected. The Erratum to this chapter is available at DOI: 10.1007/978-0-387-35658-7_21
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© 2003 IFIP International Federation for Information Processing
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Matsukura, T., Kondo, H., Hirata, Y., Tanaka, K. (2003). Discovery of Semantic Relationships among Web Pages Based on Web Topic Structures. In: Meersman, R., Aberer, K., Dillon, T. (eds) Semantic Issues in E-Commerce Systems. IFIP - The International Federation for Information Processing, vol 111. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-35658-7_11
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DOI: https://doi.org/10.1007/978-0-387-35658-7_11
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4757-1035-9
Online ISBN: 978-0-387-35658-7
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