Abstract

With the rise of e-commerce in the Internet industry, e-commerce recommendation system has been widely concerned. Electrical contractor recommendation system is based on the user's personal information such as features, historical behavior and items through collaborative filtering, content filtering, knowledge discovery, interactive and recommend recommendation technology, referring users to the items that may be of interest, in many recommendation algorithm, collaborative filtering recommendation technology is currently one of the most widely used recommendation algorithm, this paper test the collaborative filtering algorithm in the application of mobile electronic commerce recommendation system experiment, it is concluded that the realization of the collaborative filtering algorithm is better personalized recommendation.

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