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http://dx.doi.org/10.7472/jksii.2015.16.3.59

User Perspective Website Clustering for Site Portfolio Construction  

Kim, Mingyu (Graduate School of Business IT, Kookmin University)
Kim, Namgyu (School of Management Information Systems, Kookmin University)
Publication Information
Journal of Internet Computing and Services / v.16, no.3, 2015 , pp. 59-69 More about this Journal
Abstract
Many users visit websites every day to perform information retrieval, shopping, and community activities. On the other hand, there is intense competition among sites which attempt to profit from the Internet users. Thus, the owners or marketing officers of each site try to design a variety of marketing strategies including cooperation with other sites. Through such cooperation, a site can share customers' information, mileage points, and hyperlinks with other sites. To create effective cooperation, it is crucial to choose an appropriate partner site that may have many potential customers. Unfortunately, it is exceedingly difficult to identify such an appropriate partner among the vast number of sites. In this paper, therefore, we devise a new methodology for recommending appropriate partner sites to each site. For this purpose, we perform site clustering from the perspective of visitors' similarities, and then identify a group of sites that has a number of common customers. We then analyze the potential for the practical use of the proposed methodology through its application to approximately 140 million actual site browsing histories.
Keywords
Bigdata Analysis; Site Category Analysis; Site Clustering; Web Log Analysis;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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1 Survey on the Internet Usage, www.kisa.or.kr, 2013.
2 D. Y. Kim, G. G. Lim, and D. C. Lee, "A Study on the Efficiency of Internet Keyword Advertisement According to CPM and CPC Methods by Analyzing Transactional Data," Journal of the Society for e-Business Studies, Vol. 16, No.4, pp.139-152, 2011. http://dx.doi.org/10.7838/jsebs.2011.16.4.139   DOI   ScienceOn
3 C. W. Oh, "Study of the Characteristics of Internet Keyword Advertising Rate System and It's Unfair Click Types," The Korean Journal of Advertising, Vol. 19, No. 4, pp.7-27, 2008. http://www.earticle.net/article.aspx?sn=78663
4 M. G. Kim, N. G. Kim, and I. H. Jung, "A Methodology for Extracting Shopping-Related Keywords by Analyzing Internet Navigation Patterns," Journal of Intelligence and Information Systems, Vol. 20, No. 2, pp. 123-136, 2014. http://www.dbpia.co.kr/Article/3459834   DOI
5 D. Y. Jung, "The Optimal Positioning Strategy for Auction-Based CPC Advertising," Korea Internet e-Commerce Association, Vol. 6, No. 2, pp. 81-101, 2006. http://www.dbpia.co.kr/Article/615120
6 Y. S. Choi, "Researches of Keyword Advertisement of Domestic Portal Websites," Myongji University, 2005. http://www.riss.kr/link?id=T10691427
7 S. Y. Park and J. H. Kim, "Advertising Effectiveness on the Web: Do Targeting Methods Make a Difference?" Journal of Korean Marketing Association, Vol. 14, No. 4, pp. 159-178, 1999. http://www.dibrary.net/search/dibrary/search/jangseo/detailview_jangseo.jsp?contents_id=CNTS-00053282368&refLoc=portal&category=storage&srchFlag=Y&h_kwd=&lic_yn=Y&guCode3=#dummy
8 S. G. Carpenter and N. Kent "Consumer Preference Formation and Pio-neering Advantage," Journal of Marketing Research, Vol. 26, No. 3, pp. 285-298, 1989. http://dx.doi.org/10.2307/3151884   DOI
9 D. Bowman and H. Gatignon "Oder of Entry as a Moderator of the Effect of the Marketing Mix on Market Share," Marketing Science, Vol. 15, No. 3, pp.222-242, 1996. http://dx.doi.org/10.1287/mksc.15.3.222   DOI
10 Y. S. Sohn, Y. J. Kim, and Y. W. Lim, "Differentiation Strategies of the Late Entrant Internet Sites," Journal of Korean Marketing Association, Vol. 16, No. 3, pp. 21-43, 2001. http://www.dibrary.net/search/dibrary/search/jangseo/detailview_jangseo.jsp?contents_id=CNTS-00053282486&refLoc=portal&category=storage&srchFlag=Y&h_kwd=&lic_yn=Y&guCode3=
11 H. Leavitt, "Some Effects of Certain Communication Patterns on Group Performance," The Journal of Abnormal and Social Psychology, Vol. 46, No. 1, pp. 38-50, 1951. http://dx.doi.org/10.1037/h0057189   DOI
12 S. Wasserman and K. Faust, "Social network analysis: Methods and applications," Cambridge University Press, 1994. http://dx.doi.org/10.1525/ae.1997.24.1.219   DOI
13 K. Y. Kwahk, "Social Network Analysis," Cheongram, 2014.
14 D. R. Luce and A. Perry, "A Method of Matrix Analysis of Group Structure," Psychometrika, pp. 95-116, 1949. http://dx.doi.org/10.1007/BF02289146   DOI
15 I. de S. Pool and M. Kochen, "Contacts and Influence," Social Networks, Vol. 1, No. 1, pp. 5-51, 1978. http://dx.doi.org/10.1016/0378-8733(78)90011-4   DOI
16 T. Graepel, "Statistical Physics of Clustering Algorithms," Technical University of Berlin, 1998. http://research.microsoft.com/apps/pubs/default.aspx?id=65653
17 S. M. Lin and K. F. Johnson, "Methods of Microarray Data Analysis II," Kluwer Academic Publishers, pp 9-17, 2002. http://www.springer.com/gp/book/9781402071119
18 L. D. Sivanandini and M. M. Rai, "A Survey on Data Clustering Algorithm Based on Fuzzy Techniques," International Journal of Science and Research, Vol. 2, No. 4, pp. 246-251, 2013. http://www.ijsr.net/archive/v2i4/IJSRON2013704.pdf
19 B. H. Kim, "Agglomerative Clustering Methods based on Information Theory" Seoul National University, pp. 1-66, 2003. http://www.ebooksplash.com/documentfull/-63093/
20 Y. S. Maarek, R. Fagin, I. Z. Ben-Shaul, and D. Pelleg, "Ephemeral Document Clustering for Web Applications," IBM Research Report RJ10186, pp. 1-26, 2000. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.59.131
21 M. G. Kim and N. G. Kim, "User Perspective Website Clustering for Composing Collaborative Site Portfolio," In Proceedings of the Conference of the Korea Society of Information Technology Applications , 2014.
22 D. J. Lawrie, W. B. Croft, and A. Rosenberg, "Finding Topic Words for Hierarchical Summarization," In Proceedings of the 24th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 349-357, 2001. http://dx.doi.org/10.1145/383952.384022   DOI
23 I. D. Cho, N. G. Kim, and K. Y. Kwahk, "Recommending Core Research Keywords Using Social Network and Data Mining Analysis," Entrue Journal of Information Technology, Vol. 11, No. 1, pp. 89-99, 2012. http://www.researchgate.net/publication/264028775_Recommending_Core_and_Connecting_Keywords_of_Research_Area_Using_Social_Network_and_Data_Mining_Techniques
24 J. E. Kim, N. G. Kim, and Y. H. Cho, "User-Perspective Issue Clustering Using Multi-Layered Two-Mode Network Analysis," Journal of Intelligent Information Systems, Vol. 20, No. 2, pp. 93-107, 2014. http://dx.doi.org/10.13088/jiis.2014.20.2.093   DOI