Abstract. In order to find out the relationship of relational benefit effect of oil products on customer satisfaction, the local fractional algorithm is proposed in this paper for data analysis. It is investigated the adjustment effect of alternative brand competitiveness and customer characteristics to this mechanism. The results show that the proposed algorithm can thus improve overall system performance substantially.

Abstract. In order to find out the relationship between the price sensitivity and actual market acceptance degree of metallic materials, the database ensemble learning model is proposed in this paper. Due to the variety and class imbalance of customers, a database marketing model based on supervised clustering and ensemble learning is used for the model. The results show that the database ensemble learning model can thus improve the calculation accuracy and time-efficiency substantially.