Computer Science – Information Retrieval
Scientific paper
2010-10-19
Computer Science
Information Retrieval
4 pages. 1 figure
Scientific paper
In this paper, we determine the appropriate decay function for item-based collaborative filtering (CF). Instead of intuitive deduction, we introduce the Similarity-Signal-to-Noise-Ratio (SSNR) to quantify the impacts of rated items on current recommendations. By measuring the variation of SSNR over time, drift in user interest is well visualized and quantified. Based on the trend changes of SSNR, the piecewise decay function is thus devised and incorporated to build our time-aware CF algorithm. Experiments show that the proposed algorithm strongly outperforms the conventional item-based CF algorithm and other time-aware algorithms with various decay functions.
Jin Cihang
Liu Weiping
Wu Pei
Yeung Chi Ho
Zhang Yi-Cheng
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