Journal of Korea Multimedia Society (한국멀티미디어학회논문지)

Korea Multimedia Society (한국멀티미디어학회)
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Design and Implementation of a System for Recommending Related Content Using NoSQL

NoSQL 기반 연관 콘텐츠 추천 시스템의 설계 및 구현

  • Ko, Eun-Jeong (School of Computer and Information Engineering, Kwangwoon University) ;
  • Kim, Ho-Jun (School of Computer and Information Engineering, Kwangwoon University) ;
  • Park, Hyo-Ju (School of Computer and Information Engineering, Kwangwoon University) ;
  • Jeon, Young-Ho (School of Computer and Information Engineering, Kwangwoon University) ;
  • Lee, Ki-Hoon (School of Computer and Information Engineering, Kwangwoon University) ;
  • Shin, Saim (Korea Electronics Technology Institute)
  • Received : 2017.06.26
  • Accepted : 2017.07.19
  • Published : 2017.09.30
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Abstract

The increasing number of multimedia content offered to the user demands content recommendation. In this paper, we propose a system for recommending content related to the content that user is watching. In the proposed system, relationship information between content is generated using relationship information between representative keywords of content. Relationship information between keywords is generated by analyzing keyword collocation frequencies in Internet news corpus. In order to handle big corpus data, we design an architecture that consists of a distributed search engine and a distributed data processing engine. Furthermore, we store relationship information between keywords and relationship information between keywords and content in NoSQL to handle big relationship data. Because the query optimizer of NoSQL is not as well developed as RDBMS, we propose query optimization techniques to efficiently process complex queries for recommendation. Experimental results show that the performance is improved by up to 69 times by using the proposed techniques, especially when the number of requested related keywords is small.

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