Abstract
Applying the centrality measures from social network analysis to score web pages may well represent the essential role of pages and distribute their authorities in a web social network with complex link structures. To effectively score the pages, we propose a hybrid page scoring algorithm, called WebRank, based on the PageRank algorithm and three centrality measures including degree, betweenness, and closeness. The basis idea of WebRank is that: (1) use PageRank to accurately rank pages, and (2) apply centrality measures to compute the importance of pages in web social networks. In order to evaluate the performance of WebRank, we develop a web social network analysis system which can partition web pages into distinct groups and score them in an effective fashion. Experiments conducted on real data show that WebRank is effective at scoring web pages with less time deficiency than centrality measures based social network analysis algorithm and PageRank.
This work is partially supported by the National Science Foundation for Post-doctoral Scientists of China under Grant No. 20090461346; the Fundamental Research Funds for the Central Universities under Grant No. SWJTU09CX035; the Sichuan Youth Science and Technology Foundation of China under Grant No. 08ZQ026-016; the Sichuan Science and Technology Support Projects under Grant No. 2010GZ0123; the Innovative Application Projects of the Ministry of Public Security under Grant No. 2009YYCXSCST083; the Education Ministry Youth Fund of Humanities and Social Science of China under Grant No. 09YJCZH101.
Scientific and Technological Major Special Projects-Significant Creation of New Drugs under Grant No.2009ZX09313-024.
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Qiao, S., Peng, J., Li, H., Li, T., Liu, L., Li, H. (2010). WebRank: A Hybrid Page Scoring Approach Based on Social Network Analysis . In: Yu, J., Greco, S., Lingras, P., Wang, G., Skowron, A. (eds) Rough Set and Knowledge Technology. RSKT 2010. Lecture Notes in Computer Science(), vol 6401. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16248-0_67
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DOI: https://doi.org/10.1007/978-3-642-16248-0_67
Publisher Name: Springer, Berlin, Heidelberg
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