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Improvement of UCI Metadata and Resolution Service for Massive Contents Recommendation  

Na, Moon-Sung (한국콘텐츠진흥원 제작지원 본부)
Lee, Jae-Dong (단국대학교 컴퓨터학부 컴퓨터공학)
Publication Information
Journal of Korea Multimedia Society / v.13, no.3, 2010 , pp. 475-486 More about this Journal
Abstract
Contents Recommender System predicts user's preferences towards contents, and then recommends highly-predicted contents to user. Digital Identifier plays its part in identifying abstract works or digital contents in digital network environment. Digital Identifier could be effectively used in content-based filtering and collaborative filtering that are mainly used in Contents Recommender Systems. Therefore, this paper proposes an improvement of UCI metadata and resolution service for effective use of UCI in massive contents recommender systems. UCI metadata is expanded by adding elements such as abstract, keyword, genre, age, rate and review. Resolution service allows the operation systems to collect user preference for content by including input part of preference in a result page. This paper also designs and implements an improved UCI operation system and shows that the proposed improvement of UCI metadata and resolution service could be used for massive contents recommendation.
Keywords
Digital Identifier; Recommender System; UCI Metadata; Resolution Service; Content-based Filtering; Collaborative Filtering;
Citations & Related Records
Times Cited By KSCI : 6  (Citation Analysis)
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