计算机应用 ›› 2019, Vol. 39 ›› Issue (1): 181-185.DOI: 10.11772/j.issn.1001-9081.2018051154

• 人工智能 • 上一篇    下一篇

在线商品评论可信性评价方法

李超, 向静, 向军   

  1. 湖北民族学院 信息工程学院, 湖北 恩施 445000
  • 收稿日期:2018-06-08 修回日期:2018-09-05 出版日期:2019-01-10 发布日期:2019-01-21
  • 通讯作者: 李超
  • 作者简介:李超(1979-),男,湖北恩施人,副教授,博士,主要研究方向:数据挖掘、数据质量管理;向静(1978-),女,湖北恩施人,讲师,硕士,主要研究方向:知识工程;向军(1978-),男,湖北恩施人,副教授,博士,主要研究方向:移动数据质量管理。
  • 基金资助:
    国家自然科学基金资助项目(61040006);湖北省自然科学基金资助项目(2018CFB451);湖北省教育厅项目(B2014245);湖北民族学院博士基金资助项目(MY2017B019)。

Assessment method of credibility on online product reviews

LI Chao, XIANG Jing, XIANG Jun   

  1. Information Engineering College, Hubei University for Nationalities, Enshi Hubei 445000, China
  • Received:2018-06-08 Revised:2018-09-05 Online:2019-01-10 Published:2019-01-21
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (61040006), the Natural Science Foundation of Hubei Province (2018CFB451), the Education Department of Hubei Province (B2014245), the Doctor Foundation of Hubei University for Nationalities (MY2017B019).

摘要: 针对现有商品评论存在数量大、质量参差不齐、可信度差,导致用户难以快速获取有效信息并制定高效的决策,而现有评论可信性评估主要考虑评论来源和投票形式的支持度等问题,提出了一种从评论内在质量角度实现评论可信度评估方法,即通过融合评论者等级、评论支持度和评论观点一致性等实现评论可信性评估。首先基于规则库和方法库完成了评论数据的预处理;然后基于商品特征库、通用词典、情感词典以及方法库,完成了商品特征识别和特征值提取及标准化;最后基于建立的模型完成评论可信度评估。实验结果验证了该方法的可行性,该方法可以应用于其他电商平台实现商品评论可信性自动评估。

关键词: 商品评论, 评论质量, 可信性, 一致性, 质量评估

Abstract: Since there are many troubles such as large quantity, uneven quality and poor credibility in getting helpful information and making effective decision for stakeholders, and the existing research work on credibility assessment mainly considers the sources of reviews and the support of reviews in form of votes, an assessment method on review credibility from perspective of intrinsic quality was proposed. That is, the credibility assessment of reviews was realized by integrating the ratings of reviewers, the support degree of reviews and the consistency in reviews, etc. Firstly, the pre-processing of review data was completed based on rule and method libraries. Then, the feature recognition and the feature value extraction and standardization were completed based on product feature library, generic dictionary, sentiment dictionary and method library. Finally, the credibility assessment of reviews was completed based on the established models. The experimental results verify the feasibility of this method, and it can be applied to assess the credibility of product reviews automatically on other e-commerce platforms.

Key words: product review, review quality, credibility, consistency, quality assessment

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