Research on Synthetic Evaluation of Personalized Satisfaction Degree for the Ready-to-wear Online Shopping Based on Interval Algorithm and Gray Correlation Analysis

Considering the inconsistent specifications of the ready-to-wear and the customer's diverse preference for color, brand, and style, etc., a synthetic evaluation method of personalized satisfaction degree for the ready-to-wear online shopping is proposed on the basis of the interval algorithm and grey correlation analysis and its realization process is presented in detail. The idea of Internal Arithmetic method is introduced to expressing the personalized dressing preference evaluation; and the Gray Correlation Analysis method is employed to compute the individual fitness degree for the optional ready-to-wear. The synthetic evaluation results are obtained by combining the above two aspects. Finally, a case is studied to verify the feasibility and effectiveness of the proposed method. As the result shows, it can provide scientific decision-making references for the buyers' personalized preference and requirements in clothing's online shopping application.