Abstract
In this paper, we propose a method called LocalRank to rank web pages by integrating the web and a user database containing information on a specific geographical area. LocalRank is a rank value for a web page to assess its relevance degree to database entries considering geographical locality and its popularity on a local web space. In our method, we first construct a linked graph structure using entries contained in the database. The nodes of this graph consist of database entries and their related web pages. The edges in the graph are composed of semantic links including geographical links between these nodes, in addition to conventional hyperlinks. Then a link analysis is performed to compute a LocalRank value for each node. LocalRank can represent user’s interest since this graph effectively integrates the web and the user database. Our experimental results for a local restaurant database shows that local web pages related to the database entries are highly ranked based on our method.
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Zhang, J., Ishikawa, Y., Kurokawa, S., Kitagawa, H. (2005). LocalRank: Ranking Web Pages Considering Geographical Locality by Integrating Web and Databases. In: Andersen, K.V., Debenham, J., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2005. Lecture Notes in Computer Science, vol 3588. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11546924_15
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DOI: https://doi.org/10.1007/11546924_15
Publisher Name: Springer, Berlin, Heidelberg
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