计算机应用 ›› 2013, Vol. 33 ›› Issue (09): 2540-2545.DOI: 10.11772/j.issn.1001-9081.2013.09.2540

• 人工智能 • 上一篇    下一篇

基于三维坐标的消费情绪本体库建立及应用

邱云飞1,林明明1,邵良杉2   

  1. 1. 辽宁工程技术大学 软件学院,辽宁 葫芦岛 125100;
    2. 辽宁工程技术大学 系统工程研究所,辽宁 葫芦岛 125100
  • 收稿日期:2013-03-18 修回日期:2013-04-23 出版日期:2013-09-01 发布日期:2013-10-18
  • 通讯作者: 林明明
  • 作者简介:邱云飞(1976-),男(蒙古族),辽宁阜新人,教授,博士,CCF会员,主要研究方向:数据挖掘、情感分析;
    林明明(1989-),女,辽宁大连人,硕士研究生,主要研究方向:数据挖掘、情感分析;
    邵良杉(1961-),男,辽宁凌源人,教授,博士生导师,主要研究方向:数据挖掘、情感分析。
  • 基金资助:

    国家自然科学基金资助项目;辽宁省高等学校创新团队支持计划项目;辽宁省高等学校杰出青年学者成长计划项目

Establishment and application of consumption sentiment ontology library based on three-dimensional coordinate

QIU Yunfei1,LIN Mingming1,SHAO Liangshan2   

  1. 1. School of Software, Liaoning Technical University, Huludao Liaoning 125100, China;
    2. System Engineering Institute, Liaoning Technical University, Huludao Liaoning 125100, China
  • Received:2013-03-18 Revised:2013-04-23 Online:2013-10-18 Published:2013-09-01
  • Contact: LIN Mingming
  • Supported by:

    ;Liaoning innovation team project

摘要: 针对商家好评中存在非真正满意的评价问题,构建一种能够真正反映消费者情绪状态的方法,以减少好评率中非真正满意的评价。针对消费情绪进行了研究,首先从评价中提取出消费情绪词汇,根据消费情绪的特征,将消费情绪划分为7大类,25小类,建立了三维坐标模型;其次,用Protégé来构建消费情绪本体库,根据三维坐标词汇分类算法对消费情绪词汇进行自动划分;然后,根据构建的本体库,用消费情绪判断算法来自动判断消费者的评价。最后,与淘宝的好评率进行比较,F值达到了95%以上,减少了好评中非真正满意的评价,体现了消费者的真实情绪。

关键词: 消费情绪, 词汇分类, 三维坐标, 本体库, 评价

Abstract: Since the positive comments may have the non-truly satisfied comments, a method which can truly reflect the sentiment of the consumers was constructed in order to decrease the non-truly satisfied comments from the positive comments. The research oriented to the consumption sentiment shows that the consumption sentiment vocabulary should be extracted at first. According to the consumption sentimental features, consumption sentiment got classified into seven classes and twenty-five subclasses, and the three-dimensional coordinate model was established. Afterwards, Protégé was used to build a consumption sentiment ontology library so that the consumption sentiment can be automatically classified by the three-dimensional coordinate vocabulary classification algorithm. Moreover, the consumption sentiment judging algorithm was applied to automatically judge consumer comments based on the completed library. Finally, compared with the positive comment ratio of Taobao, the F-measure can reach more than 95%. It can eliminate the non-truly satisfied comments from positive comments and reflect the consumer's real emotion.

Key words: consumption sentiment, vocabulary classification, three-dimensional coordinate, ontology library, comment

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