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中文软件评论挖掘系统的设计与实现 被引量：6

Design and implementation of Chinese software reviews mining system
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摘要 为了从用户评论中及时、准确的获取用户群体对软件及服务的满意度,从而发现用户期望,为软件的改进提供依据,实现了一个对中文软件评论进行情感倾向性分析的系统。系统从网络上收集软件的用户评论数据,通过无监督的方法识别出评论中的用户关注点和情感倾向,将结果以可视化的方式展现给开发者。通过在真实数据上的测试,表明了该系统的有效性。 In order to obtain users＇ satisfaction from users~ reviews timely and accurately, and then help software developers to understand users true demands and offer reference for software improvement, an opinion mining system for Chinese software re- views is implemented. The system collects software reviews on the internet, and then identifies the user concerns and the senti- ment tendency by unsurprised method. Finally, the reviews mining results are shown to software developers with visual inter- face. Experimental results on real data sets demonstrate the validity of the system.
作者 文涛 杨达 李娟
机构地区 中国科学院软件研究所互联网软件技术实验室
出处 《计算机工程与设计》 CSCD 北大核心 2013年第1期163-167,共5页 Computer Engineering and Design
基金 国家自然科学基金项目(60803023、60903050、61100071、60873072) 国家973重点基础研究发展计划基金项目(2007CB310802)
关键词 中文软件评论 意见挖掘 软件特征 观点词 情感倾向 Chinese software reviews~ opinion mining~ software feature~ opinion word~ sentiment orientation~
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
  • 相关文献

参考文献5

  • 1李实,李秋实.中文评论中产品特征挖掘的剪枝算法研究[J].计算机工程,2011,37(23):43-45. 被引量：8
  • 2Liu B,Hu M,Cheng J.Opinion observer:analyzing and comparing opinions on the web[].Proceeding of theth international conference on World Wide Web.2005
  • 3M. Hu,B. Liu.Opinion extraction and summarization on the web[].Proceedings of the st national conference on Artificial intelligence (AAAI’’).2006
  • 4LI Shi,LI Qiushi.Improving the performance of features ex-traction from Chinese customer reviews[].The th International Conference on Communication SystemsNetworks and Applications.2010
  • 5朱嫣岚,闵锦,周雅倩,黄萱菁,吴立德.基于HowNet的词汇语义倾向计算[J].中文信息学报,2006,20(1):14-20. 被引量：326

二级参考文献15

  • 1Hu Minqing, Liu Bing. Mining Opinion Features in Customer Reviews[C]//Proc. of the 19th National Conference on Artificial Intelligence. [S. l.]: ACM Press, 2004: 755-760.
  • 2Popescu A M, Etzioni O. Extracting Product Features and Opinions from Reviews[C]//Proc. of Conference on Human Language Technology and Empirical Methods in Natural Language Processing. Vancouver, Canada: ACL Press, 2005: 339-346.
  • 3Liu Jian, Wu Gengfeng, Yao Jianxin. Opinion Searching in Multiproduct Reviews[C]//Proc. of the 6th IEEE International Conference on Computer and Information Technology. Seoul, Korea: IEEE Press, 2006: 25-30.
  • 4Shi Bin, Chang Kuiyu. Mining Chinese Reviews[C]//Proc. of the 6th IEEE International Conference on Data Mining. Hong Kong, China: IEEE Press, 2006: 585-589.
  • 5Vasileios Hatzivassiloglou, Kathleen R. McKeown. Predicting the semantic orientation of adjectives[A]. In: Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and the 8th Conference of the European Chapter of the ACL[C], 1997:174- 181.
  • 6Turney, Peter, Littman Michael. Measuring praise and criticism: Inference of semantic orientation from association[J]. ACM Transactions on Information Systems, 2003, 21(4): 315- 346.
  • 7Turney ,Peter. Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews[A]. In: Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics[C]. 2002:417 -424.
  • 8Bo Pang,Lillian Lee, Shivanathan Vaithyanathan. Thumbs up? Sentiment classification using machine learning techniques[A]. In Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing[C]. 2002:79 - 86.
  • 9Bo Pang,Lillian Lee. Seeing Stars: Exploiting Class Relationships for Sentiment Categorizalion with respect to Rating Seales[A]. ACL2005, 115-124.
  • 10K Dave, S lawrence, DM Pennock. , Mining the peanut gallery: opinion extraction and semantic classification of product reviews[A]. WWW2003, 519-28.

共引文献332

同被引文献58

  • 1谌志群,张国煊.文本挖掘与中文文本挖掘模型研究[J].情报科学,2007,25(7):1046-1051. 被引量：51
  • 2Liu Bing, Hu Minqing, Cheng Junsheng.Opinion observer: Analyzing and comparing opinions on the Web[C]// Proceedings of the 14th International Conference on World Wide Web.2005:342-351.
  • 3Hu Minqing, Liu Bing.Mining and summarizing customer reviews[C]// Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.2004:168-177.
  • 4Turney P.Thumbs up or thumbs down? Semantic orientation applied to unsupervised classification of reviews[C]// Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics.2002:417-424.
  • 5Popescu A-M, Etzioni O.Extracting product features and opinions from reviews[C]// Proceedings of the 2005 Conference on Human Language Technology and Empirical Methods in Natural Language Processing.2005:339-346.
  • 6Hu Minqing, Liu Bing.Mining opinion features in customer reviews[C]// Proceedings of the 19th AAAI National Conference on Artificial Intelligence.2004:755-760.
  • 7Ghani R, Probst K, Liu Yan, et al.Fano: Text mining for product attribute extraction[J].ACM SIGKDD Explorations Newsletter, 2006,8(1):41-48.
  • 8Ding Xiaowen, Liu Bing.The utility of linguistic rules in opinion mining[C]// Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval.2007:811-812.
  • 9Gamon M, Aue A, Corston-Oliver S, et al.Pulse: Mining customer opinions from free text[C]// Proceedings of the 6th International Symposium on Intelligent Data Analysis.2005:121-132.
  • 10Scaffidi C, Bierhoff K, Chang E, et al.Red opal: Product-feature scoring from reviews[C]// Proceedings of the 8th ACM Conference on Electronic Commerce.2007:182-191.

引证文献6

二级引证文献17

计算机工程与设计
2013年 第1期

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