A Study on Scientific Article Recommendation System with User Profile Applying TPIPF (TPIPF로 계산된 이용자프로파일을 적용한 논문추천시스템에 대한 연구)

Lingling Zhang (장령령); Chang Woo kwon (장우권)

doi:10.3743/KOSIM.2016.33.1.317

A Study on Scientific Article Recommendation System with User Profile Applying TPIPF

Journal of the Korean Society for Information Management
Abbr : JKOSIM
2016, 33(1), pp.317~336
DOI : 10.3743/KOSIM.2016.33.1.317
Publisher : 한국정보관리학회
Research Area : Interdisciplinary Studies > Library and Information Science
Received : March 5, 2016
Accepted : March 22, 2016
Published : March 30, 2016

Lingling Zhang ¹, Chang Woo kwon ²

¹전남대학교 문헌정보학과
²전남대학교

Accredited

ABSTRACT

Nowadays users spend more time and effort to find what they want because of information overload. To solve the problem, scientific article recommendation system analyse users’ needs and recommend them proper articles. However, most of the scientific article recommendation systems neglected the core part, user profile. Therefore, in this paper, instead of mean which applied in user profile in previous studies, New TPIPF (Topic Proportion-Inverse Paper Frequency) was applied to scientific article recommendation system. Moreover, the accuracy of two scientific article recommendation systems with above different methods was compared with experiments of public dataset from online reference manager, CiteULike. As a result, the proposed scientific article recommendation system with TPIPF was proven to be better.

KEYWORDS

scientific article recommendation system, article profile, user profile, TPIPF, content-based filtering, LDA

Citation status

* References for papers published after 2023 are currently being built.

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Journal of the Korean Society for Information Management 2023 KCI Impact Factor : 1.31

A Study on Scientific Article Recommendation System with User Profile Applying TPIPF

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Citation status

* References for papers published after 2023 are currently being built.

Journal of the Korean Society for Information Management 2023 KCI Impact Factor : 1.31

A Study on Scientific Article Recommendation System with User Profile Applying TPIPF

ABSTRACT

KEYWORDS

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* References for papers published after 2023 are currently being built.