关键词: 文本挖掘, 维度抽取, 维度权重, 情感分析

Abstract: Generally speaking, product reviews will refer to several dimensions of a product, each of which may have different sentiments. Actually, users have different concerns about the product. The dimensions that users care more should have more influence on the overall sentiment. Fine-grained dimension mining from reviews and dimension-level sentiment analysis can provide a lot of valuable information about market feedback and users?? preference. Unfortunately, many E-commerce platforms are lack of these significant data. This paper aims at mining the dimensions based on rules, along with their sentiments, referred by online product reviews. Next, this paper proposes the method to determine the weights of each product dimension. Then, the overall sentiment of a review can be concluded with the dimension sentiments and their corresponding weights. This paper conducts comprehensive experiments based on the real reviews from JD.com. The experimental results show that the proposed algorithm has a good performance in dimension extraction, dimension sentiment mining, weight calculation and overall sentiment determination.

Key words:  text mining, dimension mining, dimension weight, sentiment analysis