바로가기메뉴

본문 바로가기 주메뉴 바로가기

한국비블리아학회지

Article Contents

Prev
e-Submission

Vol.28 No.4
Citation Share

Personal Recommendation Service Design Through Big Data Analysis on Science Technology Information Service Platform

한국비블리아학회지 / 한국비블리아학회지, (P)1229-2435; (E)2799-4767
2017, v.28 no.4, pp.501-518
https://doi.org/10.14699/kbiblia.2017.28.4.501
Kim, Dou-Gyun
Kim,, D. (2017). Personal Recommendation Service Design Through Big Data Analysis on Science Technology Information Service Platform. 한국비블리아학회지, 28(4), 501-518, https://doi.org/10.14699/kbiblia.2017.28.4.501
  • Downloaded
  • Viewed
PDF Download

Abstract

Reducing the time it takes for researchers to acquire knowledge and introduce them into research activities can be regarded as an indispensable factor in improving the productivity of research. The purpose of this research is to cluster the information usage patterns of KOSEN users and to suggest optimization method of personalized recommendation service algorithm for grouped users. Based on user research activities and usage information, after identifying appropriate services and contents, we applied a Spark based big data analysis technology to derive a personal recommendation algorithm. Individual recommendation algorithms can save time to search for user information and can help to find appropriate information.

keywords
추천시스템, 개인화시스템, 과학기술정보, 빅데이터, 한민족과학기술자네트워크

한국비블리아학회지

e-Submission OA Policy