A Collaborative Filtering Recommendation Algorithm with Time Context for Learning Interest Mining

doi:10.13190/j.jbupt.2014.06.010

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2014, Vol. 37 ›› Issue (6): 49-53.doi: 10.13190/j.jbupt.2014.06.010

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A Collaborative Filtering Recommendation Algorithm with Time Context for Learning Interest Mining

E Hai-hong, SONG Mei-na, LI Chuan, JIANG Zhou-feng

School of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, China

Received:2014-04-25 Online:2014-12-28 Published:2014-10-17

Abstract

Abstract:

A time context based collaborative filtering recommendation (TCCF-LI) algorithm this paper was proposed, and students' learning interest mining from university library borrow record was implemented. The time context information was imported into the traditional collaborative filtering recommendation algorithm, in which, both interest homoplasy of large scale user groups and short-term correlation of small scale user groups was considered. Good recommendation performance was gained. According to the experiments on real dataset, TCCF-LI algorithm presents higher precision and recall rate compared with traditional recommendation algorithm.

Key words: recommender system, collaborative filtering, time context, learning interest mining

CLC Number:

TP311

E Hai-hong, SONG Mei-na, LI Chuan, JIANG Zhou-feng. A Collaborative Filtering Recommendation Algorithm with Time Context for Learning Interest Mining[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2014, 37(6): 49-53.

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A Collaborative Filtering Recommendation Algorithm with Time Context for Learning Interest Mining

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