Journal of Digital Convergence (디지털융복합연구)

The Society of Digital Policy and Management (한국디지털정책학회)
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Proposal of Content Recommend System on Insurance Company Web Site Using Collaborative Filtering

협업필터링을 활용한 보험사 웹 사이트 내의 콘텐츠 추천 시스템 제안

  • Kang, Jiyoung (Graduate School of Computer & Information Technology, Korea University) ;
  • Lim, Heuiseok (Department of Computer Science and Engineering, Korea University)
  • 강지영 (고려대학교 컴퓨터정보통신대학원) ;
  • 임희석 (고려대학교 컴퓨터학과)
  • Received : 2019.09.18
  • Accepted : 2019.11.20
  • Published : 2019.11.28
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Abstract

While many users searched for insurance information online, there were not many cases of contents recommendation researches on insurance companies' websites. Therefore, this study proposed a page recommendation system with high possibility of preference to users by utilizing page visit history of insurance companies' websites. Data was collected by using client-side storage that occurs when using a web browser. Collaborative filtering was applied to research as a recommendation technique. As a result of experiment, we showed good performance in item-based collaborative (IBCF) based on Jaccard index using binary data which means visit or not. In the future, it will be possible to implement a content recommendation system that matches the marketing strategy when used in a company by studying recommendation technology that weights items.

온라인에서 보험 정보를 찾는 이용자들이 많은 반면, 보험사 웹 사이트 콘텐츠 추천 연구 사례는 많지 않았으므로 본 연구에서는 보험사 웹 사이트의 페이지 방문 이력을 활용하여 사용자에게 선호 가능성이 높은 페이지 추천 시스템을 제안하였다. 데이터는 웹 브라우저 이용 시 발생하는 클라이언트 사이트 스토리지(Client-side storage)를 활용하여 수집하였으며, 추천 기술로는 협업 필터링(Collaborative filtering)을 연구에 적용하였다. 실험을 실시한 결과 방문여부를 의미하는 이진화된 데이터를 사용한 자카드 인덱스(Jaccard index) 기반의 아이템 기반 협업 필터링(Item-based collaborative, IBCF)에서 좋은 성능을 나타내었다. 향후에는 아이템에 가중치를 부여한 추천 기술을 연구하여, 기업에서 사용 시 마케팅 전략에 부합하는 콘텐츠 추천 시스템을 구현할 수 있을 것이다.

Keywords

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