International Journal of Advanced Culture Technology
- Volume 1 Issue 2
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- Pages.1-6
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- 2013
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- 2288-7202(pISSN)
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- 2288-7318(eISSN)
Improved Collaborative Filtering Using Entropy Weighting
- Kwon, Hyeong-Joon (School of Information and Communication Engineering, Sungkyunkwan University)
- Received : 2013.09.08
- Accepted : 2013.12.06
- Published : 2013.12.31
Abstract
In this paper, we evaluate performance of existing similarity measurement metric and propose a novel method using user's preferences information entropy to reduce MAE in memory-based collaborative recommender systems. The proposed method applies a similarity of individual inclination to traditional similarity measurement methods. We experiment on various similarity metrics under different conditions, which include an amount of data and significance weighting from n/10 to n/60, to verify the proposed method. As a result, we confirm the proposed method is robust and efficient from the viewpoint of a sparse data set, applying existing various similarity measurement methods and Significance Weighting.