JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2016, Vol. 46 ›› Issue (5): 29-36.doi: 10.6040/j.issn.1672-3961.2.2015.008

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A local collaborative filtering algorithm based on ranking recommendation tasks

HUANG Dan, WANG Zhihai, LIU Haiyang   

  1. School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China
  • Received:2015-05-16 Online:2016-10-20 Published:2015-05-16

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Abstract: Based on matrix factorization model, time factor and ranking problem, a collaborative filtering algorithm was proposed. The method relaxed the low-rank assumption of rating matrix and assumed that the rating matrix was locally low-rank,which meaned that the rating matrix was low-rank in the neighborhood of certain user-item combination. Mean reciprocal rank(MRR), an evaluation metric widely used in Information retrieval, was modified to fit the rating dataset. The evaluation metric was smoothed and simplied, and then was optimized. The algorithm was easy to parallelize and could operate on real data set. Experiments showed that this algorithm could improve recommendation performance.

Key words: time factor, matrix factorization, mean reciprocal rank, recommendation system, collaborative filtering

CLC Number: 

  • TP181
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