A New Hybrid Collaborative Filtering Algorithm

Abstract:

Considering the inaccuracy of the traditional similarity method in the k-nearest neighbor algorithm (KNN), we put forward a hybrid algorithm crossing the principal components analysis (PCA) and KNN via a fresh hybrid way. The algorithm makes use of differences in the contribution rates of features mined by PCA to build the similarity model of users. The experiment results argue that the fresh hybrid algorithm makes personalized recommendations very effective.

• Periodical: Applied Mechanics and Materials (Volumes 135-136)
• Pages: 80-86
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.135-136.80
• Online since: October 2011
• Authors: Chun Xia Yin, Qin Ke Peng
• Keywords: Collaborative Filtering (CF), K-Nearest Neighbor (KNN) Algorithm, Personalized Recommendation, Principal Component Analysis (PCA)

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