期刊文献+
任意字段
题名或关键词
题名
关键词
文摘
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息

基于特征变换的跨领域产品评论倾向性分析 被引量：6

Opinion Analysis of Cross-domain Product Review Based on Feature Transformation
在线阅读 下载PDF
导出
摘要 传统的情感倾向性分析方法主要针对同一领域的文本,对于不同领域的文本,传统方法效果较差。为解决该问题,提出一种基于特征变换的跨领域产品评论倾向性分析方法。通过领域独立词建立源领域和目标领域的领域依赖词之间的关联,将源领域的领域知识迁移到目标领域中,以解决数据分布不同造成的分类器效果下降的问题。使用产品评论文本作为语料进行实验,结果表明,在所有语料上基于支持向量机和逻辑回归方法的平均精度分别为76.61%和76.81%,均高于Baseline算法的平均结果。 Traditional sentiment analysis methods aim at same domain documents, the performance becomes worse for different domain documents. To solve this problem, this paper presents an opinion analysis method of cross-domain product reviews based on feature transformation. This proposed method builds the relevance of domain dependent words between source domain and target domain via domain independent words so that it can transfer acknowledge from the source domain to the target domain. It solves the classifier performance decreasing problem due to different data distributions. The product reviews are used as a corpus in the experiment. The average accuracies are 76.61% and 76.81% by using the methods of Support Vector Machine（SVM） and logistic regression respectively in all corpora. The results are higher than Baseline algorithm.
作者 孟佳娜 段晓东 杨亮
机构地区 大连民族学院计算机科学与工程学院 大连理工大学计算机科学与技术学院
出处 《计算机工程》 CAS CSCD 2013年第10期167-171,共5页 Computer Engineering
基金 国家自然科学基金资助项目(61202254) 中国博士后科学基金资助项目(2013M530918) 中央高校自主科研基金资助项目(DC120101081,DC120101084) 辽宁省教育厅科学研究基金资助一般项目(L2012478)
关键词 特征变换 倾向性分析 产品评论 源领域 目标领域 领域独立词 领域依赖词 feature transformation opinion analysis product review source domain target domain domain independent word domaindependent word
分类号 TP391 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献13

  • 1Chan Kam-Tong, King I. Let's Tango: Finding the Right Couple for Feature-opinion Association in Sentiment Analysis[C]//Proc. of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining. Berlin, Germany: Springer-Verlag, 2009.
  • 2Somasundran S, Wiebe J, Ruppenhofer J. Discourse Level Opinion Interpretation[C]//Proc. of the 22nd International Conference on Computational Linguistics. Manchester, UK: Is. n.], 2008.
  • 3姚天昉,程希文,徐飞玉,汉思·乌思克尔特,王睿.文本意见挖掘综述[J].中文信息学报,2008,22(3):71-80. 被引量：107
  • 4吕韶华,杨亮,林鸿飞.基于LDA模型的餐馆评论排序[J].计算机工程,2011,37(19):62-64. 被引量：8
  • 5Blitzer J, Dredze M, Pereira F. Biographies, Bollywood, Boomboxes and Blenders: Domain Adaptation for SentimentClassification[C]//Proc. of the 45th Annual Meeting of the Association of Computational Linguistics. Prague, Czech Republic: [s. n.], 2007.
  • 6Blitzer J, McDonald R R, Pereira F. Domain Adaptation with Structural Correspondence Learning[C]//Proc. of Conference on Empirical Methods in Natural Language. Sydney, Australia: [s. n.], 2006.
  • 7Sinno J P, Ni Xiaochuan, Sun Jiantao, et al. Cross-domain Sentiment Classification via Spectral Feature Alignment[C]// Proc. of the 19th International Conference on World Wide Web. New York, USA: ACM Press, 2010.
  • 8Zhang Di, Xue Guirong, Yu Yong. Iterative Reinforcement Cross-domain Text Classification[C]//Proc. of the 4th Inter- national Conference on Advanced Data Mining and Appli- cations. Chengdu, China: [s. n.], 2008.
  • 9吴琼,谭松波,张刚,段洣毅,程学旗.跨领域倾向性分析相关技术研究[J].中文信息学报,2010,24(1):77-83. 被引量：10
  • 10Meng Jiana, Lin Hongfei. Transfer Learning Based on Graph Ranking[C]//Proc. of the 9th International Conference on Fuzzy Systems and Knowledge Discovery. IS. 1.]: IEEE Press, 2012.

二级参考文献70

  • 1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：329
  • 2娄德成,姚天昉.汉语句子语义极性分析和观点抽取方法的研究[J].计算机应用,2006,26(11):2622-2625.
  • 3徐琳宏,林鸿飞,杨志豪.基于语义理解的文本倾向性识别机制[J].中文信息学报,2007,21(1):96-100. 被引量：124
  • 4赵军,许洪波,黄萱菁,谭松波,刘康,张奇.中文倾向性分析评测技术报告[C]//第一届中文倾向性分析评测会议(The First Chinese Opinion Analysis Evaluation).COAE,2008.
  • 5Weifu Du, Songbo Tan. An Iterative Reinforcement Approach for Fine-Grained Opinion Mining[C]//Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Boulder, Colorado, 2009: 486-493.
  • 6Huifeng Tang, Songbo Tan and Xueqi Cheng. A Survey on Sentiment Detection of Reviews. Expert Systems With Applications[J]. Elsevier. 2009, 36 (7) : 10760-10773.
  • 7Chang CC, Lin CJ. LIBSVM: a library for supportvector machines. 2001. Software available at http:// www. csie. ntu. edu. tw/-cjlin/libsvm.
  • 8Songbo Tan, Xueqi Cheng, Moustafa M. Ghanem, Bin Wang, Hongbo Xu. A Novel Refinement Approach for Text Categorization[C]//Proceedings of the 14^th ACM international conference on Information and knowledge management. Bremen, Germany, 2005: 469-476.
  • 9Songbo Tan. An Effective Refinement Strategy for KNN Text Classifier. Expert Systems With Applications[J]. Elsevier. 2006, 30(2): 290-298.
  • 10Tan S. B. Neighbor-weighted K nearest neighbor for unbalanced text corpus[J]. Expert Systems with Applications. 2005, 28: 667-671.

共引文献124

同被引文献26

  • 1侯少龙,赵政文.面向微博平台的产品市场分析模型研究[J].微型电脑应用,2011(4):4-6. 被引量：5
  • 2Scheirer W J, Rocha A R, Sapkota A, et al. Toward Open Set Recognition [ J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013,35 ( 7 ) : 1757- 1772.
  • 3Pan S J,Yang Qiang. A Survey on Transfer Learning [ J ]. IEEE Transactions on Knowledge and Data Engineering, 2010,22(10) :1345-1359.
  • 4Long Mingsheng,Wang Jianmin, Ding Guiguang, et al. Transfer Feature Learning with Joint Distribution Adaptation[C]//Proceedings of International Conference on Computer Vision. Washington D. C. ,USA: IEEE Press, 2013:2200-2207.
  • 5Gretton A,Borgwardt K M, Rasch M J, et al. A Kernel Method for the Two-Sample-Problem [ C ]//Proceedings of Advances in Neural Information Processing Systems. Washington D. C. , USA : IEEE Press, 2006 : 513 -520.
  • 6Pan S J,Tsang I W, Kwok J T, et al. Domain Adaptation via Transfer Component Analysis [ J ]. IEEE Transactions on Neural Networks ,2011,22 ( 2 ) : 199-210.
  • 7Long Mingsheng,Ding Guiguang, Wang Jianmin, et al. Transfer Sparse Coding for Robust Image Representa- tion [ C ]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Washington D. C., USA :IEEE Press ,2013:407-414.
  • 8Long Mingsheng, Wang Jianmin, Sun Jiaguang, et al. Domain Invariant Transfer Kernel Learning [ J ]. IEEE Transactions on Knowledge and Data Engineering,2014, 27(6) :1519-1532.
  • 9Shwartz S S, Tewari A. Stochastic Methods for L1- regularized Loss Minimization[ C ]//Proceedings of Inter- national Conference on Machine Learning. New York, USA: ACM Press ,2009 : 117-936.
  • 10Yuan Guoxun, Chang Kaiwei, Hsieh C, et al. A Com- parison of Optimization Methods and Software for Large-scale Ll-regularized Linear Classification [ J ]. Journal of Machine Learning Research,2010,11:3183-3234.

引证文献6

二级引证文献33

计算机工程
2013年 第10期

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部