SimCS: An Effective Method to Compute Similarity of Scientific Papers Based on Contribution Scores
- Authors
- Hamedani, Masoud Reyhani; Kim, Sang-Wook
- Issue Date
- Dec-2015
- Publisher
- IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
- Keywords
- author dominance; citations; content; contribution score; scientific papers
- Citation
- IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, v.E98D, no.12, pp.2328 - 2332
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
- Volume
- E98D
- Number
- 12
- Start Page
- 2328
- End Page
- 2332
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/155746
- DOI
- 10.1587/transinf.2015EDL8131
- ISSN
- 1745-1361
- Abstract
- In this paper, we propose SimCS (similarity based on contribution scores) to compute the similarity of scientific papers. For similarity computation, we exploit a notion of a contribution score that indicates how much a paper contributes to another paper citing it. Also, we consider the author dominance of papers in computing contribution scores. We perform extensive experiments with a real-world dataset to show the superiority of SimCS. In comparison with SimCC, the-state-of-the-art method, SimCS not only requires no extra parameter tuning but also shows higher accuracy in similarity computation.
- Files in This Item
-
Go to Link
- Appears in
Collections - 서울 공과대학 > 서울 컴퓨터소프트웨어학부 > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.