Personalized Context-Aware Collaborative Filtering Based on Neural Network and Slope One
Currently, context has been identified as an important factor in recommender systems. Lots of researches have been done for context-aware collaborative filtering (CF) recommendation, but the contextual parameters in current approaches have same weights for all users. In this paper we propose an approach to learn the weights of contextual parameters for every user based on back-propagation (BP) neural network (NN). Then we present how to predict ratings based on well-known Slope One CF to achieve personalized context-aware (PC-aware) recommendation. Finally, we experimentally evaluate our approach and compare it to Slope One and context-aware CF. The experiment shows that our approach provide better recommendation results than them.
KeywordsRecommendation Context Neural Network Collaborative Filtering Personalization
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