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

  • Journal of the Korean Biblia Society for Library and Information Science
  • 2017, 28(4), pp.501-518
  • DOI : 10.14699/kbiblia.2017.28.4.501
  • Publisher : Journal Of The Korean Biblia Society For Library And Information Science
  • Research Area : Interdisciplinary Studies > Library and Information Science

Dou Gyun Kim 1

1한국과학기술정보연구원

Accredited

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.

Citation status

* References for papers published after 2022 are currently being built.

This paper was written with support from the National Research Foundation of Korea.