Leveraging Product Adopter Information from Online Reviews for Product Recommendation
Jinpeng Wang, Wayne Xin Zhao, Yulan He, Xiaoming Li · Proceedings of the International AAAI Conference on Web and Social Media · 2021
The availability of the sheer volume of online product reviews makes it possible to derive implicit demographic information of product adopters from review documents. This paper proposes a novel approach to the extraction of product adopter mentions from online reviews. The extracted product adopters are then categorise into a number of different demographic user groups. The aggregated demographic information of many product adopters can be used to characterise both products and users, which can be incorporated into a recommendation method using weighted regularised matrix factorisation. Our experimental results on over 15 million reviews crawled from JINGDONG, the largest B2C e-commerce website in China, show the feasibility and effectiveness of our proposed framework for product recommendation.