Reduction of Data Sparsity in Collaborative Filtering based on Fuzzy Inference Rules

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Provided by: Accent Social and Welfare Society
Topic: Mobility
Format: PDF
Collaborative filtering recommender system plays a very demanding and significance role in this era of internet information and of course e commerce age. Collaborative filtering predicts user preferences from past user behavior or user-item relationships. Though it has many advantages it also has some limitations such as sparsity, scalability, accuracy, cold start problem, etc. In this paper, the authors proposed a method that helps in reducing sparsity to enhance recommendation accuracy. They developed fuzzy inference rules which is easily to implement and also gives better result.
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