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http://dx.doi.org/10.14400/JDC.2019.17.11.201

Proposal of Content Recommend System on Insurance Company Web Site Using Collaborative Filtering  

Kang, Jiyoung (Graduate School of Computer & Information Technology, Korea University)
Lim, Heuiseok (Department of Computer Science and Engineering, Korea University)
Publication Information
Journal of Digital Convergence / v.17, no.11, 2019 , pp. 201-206 More about this Journal
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.
Keywords
Recommendation system; Collaborative filtering; IBCF; Jaccard index; Client-side storage;
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Times Cited By KSCI : 3  (Citation Analysis)
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