A Personalized Recommendation Model in E Commerce Based on TOPSIS Algorithm

From the perspective of performance and universality, this paper analyzed the characteristics of typical technologies for personalized recommendation system, and then made a basic architecture for the improved model. With the architecture, this paper introduced a personalized recommendation model in e-commerce system. The model is based on an n-tiers structure and the TOPSIS algorithm, first standardize the user evaluation indexes, and then determine the indexes weights according to user's needs, and finally calculate the personalized recommendation results. This model can be applied to a variety of e-commerce applications, especially for the e-commerce application with structured or semi-structured products such as digital books, journals and other publications.