In many e-commerce cases, the number of the goods which can be displayed in the promotional webpage is very limited. The sellers cannot put all the goods displayed in the front webpage of the promotion, and they won't waste the valuable opportunity to randomly place some ones. It is an urgent problem for the sellers that how to pick out the most appropriate goods to be laid out in the front promotional webpage among the number of merchandise. In order to provide the optimal strategy to the sellers, we firstly analyze their major concerns in promotional activities: to pursue the maximum profit, to dominate the extensive market, and to win the best reputation. We also make a study of the promotional characteristics, including the effect of earning power and cross selling, the influence of price discount and the reputation based on customer sentiment analysis. Then, an EPR (Earning power-Price discount - Reputation) model based TOPSIS is built, and the extended genetic algorithm is used to solve the problem. At last, an experiment is carried out in this paper to show the effectiveness of the solution.
Building behavioral AI using trust and reputation model based on mask model.
