Collaborative Filtering Algorithm Based on Weighted Information Entropy Similarity
Qiangqiang Zhu · Journal of Zhengzhou University · 2012
Collaborative filtering algorithm is one of the most successful recommender system technology.The similarity calculation is the core of the collaborative filtering algorithm.In view of the poor predication quality existing in traditional similarity calculation with sparse data,we propose a similarity calculation method based on the information entropy between differences of items.First,we weight the entropy by the difference and common evaluation and then normalized it to measure the similarity between items.Verified by experiments with item-based collaborative filtering algorithm,the results show that it improves accuracy of personalized recommendation.