Abstract
Over the past few years, more and more consumers have come to read online reviews when they shop online. To support consumers' purchase decisions, many scholars focus on ranking products based on online reviews and propose various methods and techniques. Generally, the process of information fusion for ranking products based on online reviews consists of three stages: product feature extraction, sentiment analysis, and ranking products. In this paper, we review the existing studies on processes and methods of information fusion for each stage. Furthermore, we briefly review the existing research on information fusion based on online reviews in other fields. Finally, we summarize the main conclusions of this paper and point out the future research direction.
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