Abstract
This paper describes a system for collecting Web pages that are relevant to a particular topic through an interactive approach. Indicated some relevant pages by a user, this system automatically constructs a set of rules to find new relevant pages. The purpose of the system is to reduce users’ browsing cost by filtering non-relevant pages automatically. Such an approach can be useful when users do not know how to describe their requirements to search engines. We describe the representation and the learning algorithm, and also show the experiments comparing its performance with a search engine.
Japan Science and Technology Corporation
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© 2001 Springer-Verlag Berlin Heidelberg
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Okabe, M., Yamada, S. (2001). Interactive Web Page Filtering with Relational Learning. In: Zhong, N., Yao, Y., Liu, J., Ohsuga, S. (eds) Web Intelligence: Research and Development. WI 2001. Lecture Notes in Computer Science(), vol 2198. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45490-X_57
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DOI: https://doi.org/10.1007/3-540-45490-X_57
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42730-8
Online ISBN: 978-3-540-45490-8
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