Abstract
Hyperlink, or shortly link, analysis seeks to model the web structures and discover the relations among web sites or Web pages. The extracted models or relations can be used for the web mining applications, including market researches and various online businesses. It is well known that PageRank of Google’s search engine is one of the most successful stories of link analysis. In this paper, we investigate into the link structures among the sites, each of which is the collection of web pages in the same university domain in Korea. However, the PageRank algorithm cannot be directly applied to the ranking of a relatively small number of sites or communities since the transition probabilities from a node with a low out-degree significantly affect the whole rankings among the sites. We modify the original version of the PageRank algorithm in order to make it fit into the site ranking, we propose a site ranking algorithm, which is a modification of the PageRank algorithm. The experimental results show that our approach to the site ranking performs much better than PageRank.
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© 2007 Springer-Verlag Berlin Heidelberg
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Kim, K., Kang, M., Choi, Y. (2007). A Site-Ranking Algorithm for a Small Group of Sites. In: Gervasi, O., Gavrilova, M.L. (eds) Computational Science and Its Applications – ICCSA 2007. ICCSA 2007. Lecture Notes in Computer Science, vol 4706. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74477-1_37
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DOI: https://doi.org/10.1007/978-3-540-74477-1_37
Publisher Name: Springer, Berlin, Heidelberg
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