Computer Engineering and Applications ›› 2019, Vol. 55 ›› Issue (19): 235-245.DOI: 10.3778/j.issn.1002-8331.1901-0191

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Online Reviews Mining for Product Design Improvement

WANG Keqin, WU Fengjun   

  1. School of Management, Northwestern Polytechnical University, Xi’an 710072, China
  • Online:2019-10-01 Published:2019-09-30



  1. 西北工业大学 管理学院,西安 710072

Abstract: From the perspective of product design improvements, by taking the product online reviews in the competitive market environment as the research object, the data mining methods and tools are adopted to conduct online reviews big data analysis for design improvement. The focus is on usefulness analysis modeling and feature evaluation value for sentiment analysis in online reviews data mining process model. According to this process, a case study of a smart phone product is conducted, and the evaluation values of various attributes of the product are obtained. Comparing with those of the updated product, the effectiveness of the proposed method is verified.

Key words: product design improvement, online reviews mining, usefulness model, sentiment analysis, feature evaluation value

摘要: 以竞争市场环境中的产品在线评论数据为研究对象,基于支持产品设计改进的视角,采用数据挖掘的方法与工具,开展面向产品设计改进的在线评论大数据分析研究。重点开展在线评论数据挖掘过程模型中的有用性建模和特征评价值情感分析。以某智能手机产品的在线评论数据为对象进行了实验,得到该产品各个属性的评价值,与更新换代后的产品属性进行比较,验证了此方法的有效性。

关键词: 产品设计改进, 在线评论挖掘, 有用性建模, 情感分析, 特征评价值