Abstract
Link analysis is one of the most effective methods of web structure mining. Traditional link analysis methods only consider the flat structure of the web with hyperlinks. It may affect the precision of the analysis result inevitably. It is observed that the web could be treated as an entity with a three-layer structure: host layer, page layer and block layer. Considering this three-layer structure is expected to improve the precision significantly when performing link analysis. A novel algorithm, three-layer based ranking is proposed to complete this task. In this algorithm, the important hosts and blocks are found within adaptations of the traditional link analysis methods. Based on these hosts and blocks, the web pages both belonged to important hosts and containing important blocks could be retrieved. These web pages are just the authoritative web pages that link analysis is looking for. We experimentally evaluate the precision of our three-layer based ranking algorithm. It is concluded from extensive experiments that this method outperforms other traditional algorithms significantly.
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References
Page, L., Brin, S., Motwani, R., Winograd, T.: The PageRank Citation Ranking: Bringing Order to the Web. Technical report, Stanford University, Stanford, CA (1998)
Kleinberg, J.M.: Authoritative Sources in a Hyperlinked Environment. In: Proc. ACM-SIAM Symposium on Discrete Algorithms (1998)
Lempel, R., Moran, S.: Salsa: The Stochastic Approach for Link-Structure Analysis. ACM Transactions on Information Systems 19(2), 131–160 (2001)
Borodin, Rosenthal, J.S., Roberts, G.O., Tsaparas, P.: Link Analysis Ranking: Algorithms, Theory, and Experiments. ACM Transactions on Internet Technology 5(1), 231–297 (2005)
Xue, G.R., et al.: Exploiting the Hierarchical Structure for Link Analysis. In: SIGIR 2005, Salvador, Brazil, August 15–19 (2005)
Liu, N., Yang, C.C.: Extracting a Website’s Content Structure From its Link Structure. In: CIKM 2005, Bremen, Germany, October 31-November 5 (2005)
Kamvar, S.D., Haveliwala, T.H., Manning, C.D., Golub, G.H.: Exploiting the block structure of the web for. computating pagerank. Technical Report Technical Report, Stanford University (March 2003)
Song, R., Liu, H., Wen, J.-R., Ma, W.-Y.: Learning Block Importance Models for Web Pages. In: WWW 2004, New York, May 17-22 (2004)
Cai, D., He, X.-F., Wen, J.-R., Ma, W.-Y.: Block-level Link Analysis. In: SIGIR 2004, Sheffield, South Yorkshire, UK, July 25–29 (2004)
Cai, D., Yu, S., Wen, J.-R., Ma, W.-Y.: VIPS: a visionbased page segmentation algorithm, Microsoft Technical Report, MSR-TR-2003-79 (2003)
Huang, S., et al.: A study on combination of block importance and relevance to estimate page relevance. In: WWW 2005, Chiba, Japan, May 10-14 (2005)
Chakrabarti, S.: Integrating the Document Object Model with Hyperlinks for Enhanced Topic Distillation and Information Extraction. In: The Proceedings of the 10th World Wide Web Conference (WWW 10) (2001)
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© 2006 Springer-Verlag Berlin Heidelberg
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Wang, Q., Liu, Y., Luo, J. (2006). Exploiting Link Analysis with a Three-Layer Web Structure Model. In: Aberer, K., Peng, Z., Rundensteiner, E.A., Zhang, Y., Li, X. (eds) Web Information Systems – WISE 2006. WISE 2006. Lecture Notes in Computer Science, vol 4255. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11912873_21
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DOI: https://doi.org/10.1007/11912873_21
Publisher Name: Springer, Berlin, Heidelberg
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