Product Promotion Prediction Model Based on Evaluation Information

Kang Qixiu(College of Artificial Intelligence, North China University of Science and Technology)
Tang Jing(College of Artificial Intelligence, North China University of Science and Technology)
Wang Yuming(College of Artificial Intelligence, North China University of Science and Technology)

Abstract

This paper mainly studies the impact of evaluation information on e-commerce platform on the future of products. Through natural language processing and rating, an evaluation model based on user rating and evaluation is defined to measure product quality. Among them, evaluations are differentiated: review sentiment coefficient (R) and review length (L).The evaluation model is:D=0.3*S+0.7*( 0.3*L+0.7*R). In order to predict the future reputation of products, based on the above evaluation model, time series is used to rank the products studied. Each customer purchases the product through Markov chain model, so as to predict the probability of future word-of-mouth spread of the product. Use TOPSIS method to select monthly sales, stars and comment sentiment coefficient as indicators. The comprehensive measurement method based on text and score is determined to predict whether the product is successfully promoted.

Keywords

NLP; Markov chains; TOPSIS; Product promotion

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DOI: http://dx.doi.org/10.26549/met.v5i1.6373