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Web Mining and Social Networking: Techniques and ... - tud.ttu.ee

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202 References119. J. Hou <strong>and</strong> Y. Zhang. Constructing good quality web page communities. In ADC ’02:Proc<strong>ee</strong>dings of the 13th Australasian database conference, pages 65–74, Darlinghurst,Australia, Australia, 2002. Australian Computer Society, Inc.120. J. Hou <strong>and</strong> Y. Zhang. Effectively finding relevant web pages from linkage information.IEEE Trans. on Knowl. <strong>and</strong> Data Eng., 15(4):940–951, 2003.121. J. Hou <strong>and</strong> Y. Zhang. Utilizing hyperlink transitivity to improve web page clustering.In Proc<strong>ee</strong>dings of the 14th Australasian Database Conferences (ADC2003), volume 37,pages 49–57, Adelaide, Australia, 2003. ACS Inc.122. A. K. Jain, M. N. Murty, <strong>and</strong> P. J. Flynn. Data clustering: a review. ACM Comput. Surv.,31(3):264–323, 1999.123. K. Järvelin <strong>and</strong> J. Kekäläinen. Cumulated gain-based evaluation of ir techniques. ACMTrans. Inf. Syst., 20(4):422–446, 2002.124. G. Jeh <strong>and</strong> J. Widom. Scaling personalized web search. In Proc<strong>ee</strong>dings of the 12th InternationalWorld Wide <strong>Web</strong> Conference (WWW’03), pages 271–279, Budapest, Hungary,2003.125. F. Jelinek. Statistical methods for sp<strong>ee</strong>ch recognition. MIT Press, 1997.126. X. Jin <strong>and</strong> B. Mobasher. Using semantic similarity to enhance item-based collaborativefiltering. In in Proc<strong>ee</strong>dings of The 2nd International Conference on Information <strong>and</strong>Knowledge Sharing, 2003.127. X. Jin, Y. Zhou, <strong>and</strong> B. Mobasher. A unified approach to personalization based onprobabilistic latent semantic models of web usage <strong>and</strong> content. In Proc<strong>ee</strong>dings of theAAAI 2004 Workshop on Semantic <strong>Web</strong> Personalization (SWP’04), San Jose, 2004.128. X. Jin, Y. Zhou, <strong>and</strong> B. Mobasher. A maximum entropy web recommendation system:Combining collaborative <strong>and</strong> content features. In Proc<strong>ee</strong>dings of the ACM SIGKDDConference on Knowledge Discovery <strong>and</strong> Data <strong>Mining</strong> (KDD’05), pages 612–617,Chicago, 2005.129. T. Joachims, D. Freitag, <strong>and</strong> T. Mitchell. <strong>Web</strong>watcher: A tour guide for the world wideweb. In The 15th International Joint Conference on Artificial Intelligence (IJCAI’97),pages 770–777, Nagoya, Japan, 1997.130. M. I. Jordan, editor. Learning in graphical models. MIT Press, Cambridge, MA, USA,1999.131. N. Kaji <strong>and</strong> M. Kitsuregawa. Building lexicon for sentiment analysis from massive collectionof html documents. In Proc<strong>ee</strong>dings of the 2007 Joint Conference on EmpiricalMethods in Natural Language Processing <strong>and</strong> Computational Natural Language Learning(EMNLP-CoNLL’07), pages 1075–1083, 2007.132. M. Kamber, J. Han, <strong>and</strong> J. Chiang. Metarule-guided mining of multi-dimensional associationrules using data cubes. In Proc<strong>ee</strong>dings of ACM SIGKDD International Conferenceon Knowledge Discovery <strong>and</strong> Data <strong>Mining</strong>, pages 207–210, 1997.133. S. D. Kamvar, T. H. Haveliwala, C. D. Manning, <strong>and</strong> G. H. Golub. Extrapolation methodsfor accelerating pagerank computations. In WWW ’03: Proc<strong>ee</strong>dings of the 12thinternational conference on World Wide <strong>Web</strong>, pages 261–270, New York, NY, USA,2003. ACM.134. H. R. Kim <strong>and</strong> P. K. Chan. Learning implicit user interest hierarchy for context inpersonalization. In Proc<strong>ee</strong>dings of the 2003 International Conference on IntelligentUser Interfaces (IUI’03), pages 101–108, Miami, FL, USA, 2003.135. H.-r. Kim <strong>and</strong> P. K. Chan. Personalized ranking of search results with learned userinterest hierarchies from bookmarks. In Proc<strong>ee</strong>dings of the 7th WEBKDD workshopon Knowledge Discovery from the <strong>Web</strong> (WEBKDD’05), pages 32–43, Chicago, Illinois,USA, 2005.

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