Journal of Internet Computing and Services (인터넷정보학회논문지)

Korean Society for Internet Information (한국인터넷정보학회)
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User Perspective Website Clustering for Site Portfolio Construction

사이트 포트폴리오 구성을 위한 사용자 관점의 웹사이트 클러스터링

  • Kim, Mingyu (Graduate School of Business IT, Kookmin University) ;
  • Kim, Namgyu (School of Management Information Systems, Kookmin University)
  • Received : 2015.01.05
  • Accepted : 2015.02.16
  • Published : 2015.06.30
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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.

많은 사용자들이 인터넷을 통해 정보검색, 쇼핑, 커뮤니티 참여 등의 일상 생활을 영위하고 있으며, 이들 인터넷 사용자들로부터 수익을 창출하기 위한 웹사이트들의 경쟁은 점점 치열해지고 있다. 각 사이트의 운영자 및 마케팅 담당자들은 경쟁 우위를 차지하기 위해 다양한 전략을 수립하고 있으며, 이 과정에서 타 사이트와의 제휴가 이루어지는 경우도 비일비재하다. 이는 타 사이트와의 제휴를 통해 타사의 고객 정보를 부분적으로 공유할 수 있을 뿐 아니라 포인트 공유, 상호 추천 등 보다 다양한 전략의 운용이 가능하기 때문이다. 제휴를 통해 긍정적인 성과를 거두기 위해서는 현재 자사의 고객은 아니지만 미래의 자사 고객이 될 수 있는 잠재 고객을 다수 확보하고 있는 타 사이트를 제휴 대상으로 선정하는 것이 매우 중요하다. 하지만 많은 사이트 중 이와 같이 자사에 도움이 되는 제휴 대상 사이트를 식별하는 것은 쉬운 일이 아니다. 따라서 본 논문에서는 방문 고객의 유사성 관점에서 사이트 클러스터링을 수행하고, 이에 근거하여 유사 고객군을 공유하고 있는 제휴 사이트 대상을 식별할 수 있는 방안을 제시한다. 또한 제안 방법론의 실무적용 가능성을 평가하기 위해, 웹사이트 150,295개에 대한 패널 5,000명의 실제 방문 기록 약 1억 4천만 건에 대해 실험을 수행하고 그 결과를 제시한다.

Keywords

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