Grey-Markov model of user demands prediction based on online reviews

Users have higher demands on product with the developing e-commerce and the increasing online shopping. Enterprises must design products that meet user demands accurately and quickly to improve user satisfaction and increase product competitiveness. In the face of ever-changing user demands, enterprises need to predict the changing trend of user demands, so as to design products more in line with user demands and reduce the market risk of new product development. Therefore, this paper proposes a Grey-Markov model of user demands prediction based on online reviews for enterprises to predict the monthly changing trend of user demands in advance. Firstly, LDA topic model and sentiment analysis are used to get user attention values and user satisfaction values. Secondly, The Grey-Markov model of user demands prediction was established. According to two dimensions of the attention and satisfaction of user demands, the values of user demands are predicted, and the division of user demand improvement sequence is used to balance the scheme of product optimisation. Finally, taking the demand prediction and optimisation design of smartphones and automobiles for examples to illustrate the effectiveness of the proposed method and to provide a reference for manufacturing enterprises to optimise product design.

Automated summary

With the development of e-commerce and the increase in online shopping, users have higher demands on products. Enterprises need to design products that meet user demands accurately and quickly in order to improve user satisfaction and product competitiveness. This paper proposes a Grey-Markov model of user demands prediction based on online reviews, which predicts the monthly changing trend of user demands in advance. By using LDA topic model and sentiment analysis, user attention values and satisfaction values are obtained. The effectiveness of the proposed method is illustrated through examples of demand prediction and optimization design for smartphones and automobiles, providing a reference for manufacturing enterprises to optimize product design.