Abstract
PageRank is one of the most popular link analysis algorithms that have shown their effectiveness in web search. However, PageRank only consider hyperlink information. In this paper, we propose several novel ranking algorithms, which make use of both hyperlink and site structure information to measure the importance of each web page. Specifically, two kinds of methodologies are adopted to refine the PageRank algorithm: one combines hyperlink information and website structure information together by graph fusion to refine PageRank algorithm, while the other re-ranks the pages within the same site by quadratic optimization based on original PageRank values. Experiments show that both two methodologies effectively improve the retrieval performance.
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Yan, HM., Qin, T., Liu, TY., Zhang, XD., Feng, G., Ma, WY. (2005). Calculating Webpage Importance with Site Structure Constraints. In: Lee, G.G., Yamada, A., Meng, H., Myaeng, S.H. (eds) Information Retrieval Technology. AIRS 2005. Lecture Notes in Computer Science, vol 3689. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11562382_48
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DOI: https://doi.org/10.1007/11562382_48
Publisher Name: Springer, Berlin, Heidelberg
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