Paper Title:
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.

  Info
Periodical
Chapter
Chapter 1: Transportation & Service Science
Edited by
Robin G. Qiu and Yongfeng Ju
Pages
80-86
DOI
10.4028/www.scientific.net/AMM.135-136.80
Citation
C. X. Yin, Q. K. Peng, "A New Hybrid Collaborative Filtering Algorithm", Applied Mechanics and Materials, Vols. 135-136, pp. 80-86, 2012
Online since
October 2011
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