DocumentCode :
2026634
Title :
Claper: Recommend classical papers to beginners
Author :
Wang, Yonggang ; Zhai, Ennan ; Hu, Jianbin ; Chen, Zhong
Author_Institution :
Sch. of Electron. Eng. & Comput. Sci., Peking Univ., Beijing, China
Volume :
6
fYear :
2010
fDate :
10-12 Aug. 2010
Firstpage :
2777
Lastpage :
2781
Abstract :
Classical papers are of great help for beginners to get familiar with a new research area. However, digging them out is a difficult problem. This paper proposes Claper, a novel academic recommendation system based on two proven principles: the Principle of Download Persistence and the Principle of Citation Approaching (we prove them based on real-world datasets). The principle of download persistence indicates that classical papers have few decreasing download frequencies since they were published. The principle of citation approaching indicates that a paper which cites a classical paper is likely to cite citations of that classical paper. Our experimental results based on large-scale real-world datasets illustrate Claper can effectively recommend classical papers of high quality to beginners and thus help them enter their research areas.
Keywords :
citation analysis; recommender systems; Claper recommendation system; academic recommendation system; citation approaching principle; classical papers; download persistence principle; Computer science; Educational institutions; Electronic mail; Libraries; Measurement; Peer to peer computing; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2010 Seventh International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5931-5
Type :
conf
DOI :
10.1109/FSKD.2010.5569227
Filename :
5569227
Link To Document :
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