Research on Commodity Recommendation Algorithm Based on Collaborative Filtering
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Tong Haifeng, Zhang Chengnian, Hu Jianfeng
the Rapid Development of e-Commerce Has Led to Tremendous Changes in the Retail Industry. More and More Offline Enterprises Have Begun to Turn to Online Development, and after Experiencing the Rapid Growth of Users, They Gradually Began to Face Problems Such as Slow Growth of Users and Disappearance of e-Commerce Dividends. At the Same Time, as Incomes Increase, Consumer Demand is Increasingly Diversified. Therefore, This Paper Constructs a Collaborative Filtering Algorithm to Study Commodity Recommendation, in Order to Solve the Development Problems Faced by Enterprises and Meet the Individual Needs of Users.
Collaborative Filtering; User Characteristics; History Record; Products Featured; Algorithm