Identifying the Relative Importance of Customer Issues on Product Ratings through Machine Learning

被引:1
|
作者
Tiwari, Himanshu [1 ]
Sait, Shameed [1 ]
Rizvi, Md Imbesat Hassan [1 ]
Damera-Venkata, Niranjan [2 ]
机构
[1] HP R&D Ctr, Bangalore, Karnataka, India
[2] HP Labs, Palo Alto, CA USA
来源
PROCEEDINGS OF THE ACM SYMPOSIUM ON DOCUMENT ENGINEERING (DOCENG 2018) | 2018年
关键词
Customer Review Analysis; Attention Models;
D O I
10.1145/3209280.3229113
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Millions of customer reviews for products are available online across hundreds of different websites. These reviews have a tremendous influence on the purchase decision of new customers and in creating a positive brand image. Understanding which of the product issues are critical in determining the product ratings is crucial for marketing teams. We have developed a solution which can derive deep insights from customer reviews which goes significantly beyond keyword based analysis. Our solution can identify key customer issues voiced in the reviews and the impact of each of these on the final rating that a customer gives the product. This insight is very actionable as it helps identify which customer concerns are responsible for bad ratings of products.
引用
收藏
页数:4
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