Recommendation Algorithm for Mobile E-commerce Based on Reputation

In the new technical background, more and more goods appear in front of the user. Unfortunately, users are increasingly easy to get lost in the massive commodity information. In order to improve the users experience of mobile e-commerce, combined with the advanced technology of large data age, there have been many recommendation algorithms for mobile e-commerce. All of this recommendation algorithms based on customer interests, sales and other different considerations, in order to achieve a purposeful and efficient screening recommendation information. In many ways of thinking, the user reputation as a new era of the spirit of the contract reflects the important value. In this paper, we focus on the current technical situation, designing a set of scoring algorithm through the analysis of the previous behavioral data modeling. After this algorithm, from different customer categories of different needs to start using the mainstream for the score of the business recommendation algorithm algorithm to achieve. And the results are compared with the expected analysis in order to obtain the current algorithm in the credibility of the algorithm under the improvement and adjustment. Finally, we will design a set of recommendation algorithm based on the reputation standards.