[1]吴钟强,张耀文,商琳.基于语义特征的多视图情感分类方法[J].智能系统学报,2017,12(5):745-751.[doi:10.11992/tis.201706026]
 WU Zhongqiang,ZHANG Yaowen,SHANG Lin.Multi-view sentiment classification of microblogs based on semantic features[J].CAAI Transactions on Intelligent Systems,2017,12(5):745-751.[doi:10.11992/tis.201706026]
点击复制

基于语义特征的多视图情感分类方法

参考文献/References:
[1] LIU B. Sentiment analysis and opinion mining[J]. Synthesis lectures on human language technologies, 2012, 5(1):1-167.
[2] PANG T B, PANG B, LEE L. Thumbs up? Sentiment classification using machine learning[J].Proceedings of EMNLP, 2002:79-86.
[3] T?CKSTR?M O, MCDONALD R. Semi-supervised latent variable models for sentence-level sentiment analysis[C]//The 49th Annual Meeting of the Association for Computational Linguistics. Stroudsburg, USA, 2011:569-574.
[4] QIU G, LIU B, BU J, et al. Opinion word expansion and target extraction through double propagation[J]. Computational linguistics, 2011, 37(1):9-27.
[5] WU Y, ZAHNG Q, HUANG X, et al. Phrase Dependency Parsing for Opinion Mining[C]//Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, USA, 2009:1533-1541.
[6] LIU Y, HUANG X, AN A, et al. ARSA:a sentiment-aware model for predicting sales performance using blogs[C]//International ACM SIGIR Conference on Research and Development in Information Retrieval. New York, USA, 2007:607-614.
[7] MISHNE G, GLANCE N S. Predicting movie sales from blogger sentiment[C]//National Conference on Artificial Intelligence. Menlo Park, USA, 2006:155-158.
[8] O’CONNOR B, BALASUBRAMANYAN R, ROUTLEDGE B R, et al. From tweets to polls:linking text sentiment to public opinion time series[C]//Proceedings of the Fourth International AAAI Conference on Weblogs and Social Media. Menlo Park, USA, 2010:122-129.
[9] CHIANG H C, MOSES R L, POTTER L C. Model-based Bayesian feature matching with application to synthetic aperture radar target recognition[J]. Pattern recognition, 2001, 34(8):1539-1553.
[10] MCCULLOUGH C L. Feature and data-level fusion of infrared and visual images[J]. Proceedings of SPIE-the international society for optical engineering, 1999, 3719:312-318.
[11] YANG J, YANG J Y, ZHANG D, et al. Feature fusion:parallel strategy vs. serial strategy[J]. Pattern recognition, 2003, 36(6):1369-1381.
[12] SALTON G, WONG A, YANG C S. A vector space model for automatic indexing[M]. New York:ACM, 1975:613-620.
[13] DEERWESTER S, DUMAIS S T, FURNAS G W. Indexing by latent semantic analysis[J]. Journal of the american society for information science, 1990, 41:391-407.
[14] REHDER B, SCHREINER M E, WOLFE M B W, et al. Using latent semantic analysis to assess knowledge:some technical considerations[J]. Discourse processes, 1998, 25(2/3):337-354.
[15] GOLUB G H, REINSCH C. Singular value decomposition and least squares solutions[J]. Numerische mathematik,1970, 14(5):403-420.
[16] WANG F, PENG J, LI Y. Hypergraph based feature fusion for 3-D object retrieval[J]. Neurocomputing, 2015, 151:612-619.
[17] FARQUHAR J D R, HARDOON D R, MENG H, et al. Two view learning:SVM-2K, theory and practice[C]//International Conference on Neural Information Processing Systems. Stroud sburg, USA, 2005:355-362.
[18] ZHANG H P, YU H K, XIONG D Y, et al. HHMM-based Chinese lexical analyzer ICTCLAS[C]//Proceedings of the second SIGHAN workshop on Chinese language Processing-Volume 17. Stroudsburg, USA, 2003:758-759.
[19] TAN S, ZHANG J. An empirical study of sentiment analysis for chinese documents[J]. Expert systems with applications, 2008, 34(4):2622-2629.
[20] BLEI D M, NG A Y, JORDAN M I. Latent dirichlet allocation[J]. Journal of machine learning research, 2003, 3:993-1022.
[21] ZHAO W X, JIANG J, WENG J, et al. Comparing twitter and traditional media using topic models[J]. Lecture notes in computer science, 2011, 6611:338-349.
[22] YAN X, GUO J, LAN Y, et al. A biterm topic model for short texts[C]//Proceedings of the 22nd international conference on World Wide Web. New York, USA, 2013:1445-1456.
相似文献/References:
[1]赵文清,侯小可,沙海虹.语义规则在微博热点话题情感分析中的应用[J].智能系统学报,2014,9(1):121.[doi:10.3969/j.issn.1673-4785.201208020]
 ZHAO Wenqing,HOU Xiaoke,SHA Haihong.Application of semantic rules to sentiment analysis of microblog hot topics[J].CAAI Transactions on Intelligent Systems,2014,9():121.[doi:10.3969/j.issn.1673-4785.201208020]
[2]李海林,邹金串.基于分类词典的文本相似性度量方法[J].智能系统学报,2017,12(4):556.[doi:10.11992/tis.201608010]
 LI Hailin,ZOU Jinchuan.Text similarity measure method based on classified dictionary[J].CAAI Transactions on Intelligent Systems,2017,12():556.[doi:10.11992/tis.201608010]
[3]张森,张晨,林培光,等.基于用户查询日志的网络搜索主题分析[J].智能系统学报,2017,12(5):668.[doi:10.11992/tis.201706096]
 ZHANG Sen,ZHANG Chen,LIN Peiguang,et al.Web search topic analysis based on user search query logs[J].CAAI Transactions on Intelligent Systems,2017,12():668.[doi:10.11992/tis.201706096]
[4]曾碧卿,韩旭丽,王盛玉,等.层次化双注意力神经网络模型的情感分析研究[J].智能系统学报,2020,15(3):460.[doi:10.11992/tis.201812017]
 ZENG Biqing,HAN Xuli,WANG Shengyu,et al.Hierarchical double-attention neural networks for sentiment classification[J].CAAI Transactions on Intelligent Systems,2020,15():460.[doi:10.11992/tis.201812017]
[5]肖宇晗,林慧苹,汪权彬,等.基于双特征嵌套注意力的方面词情感分析算法[J].智能系统学报,2021,16(1):142.[doi:10.11992/tis.202012024]
 XIAO Yuhan,LIN Huiping,WANG Quanbin,et al.An algorithm for aspect-based sentiment analysis based on dual features attention-over-attention[J].CAAI Transactions on Intelligent Systems,2021,16():142.[doi:10.11992/tis.202012024]
[6]张铭泉,周辉,曹锦纲.基于注意力机制的双BERT有向情感文本分类研究[J].智能系统学报,2022,17(6):1220.[doi:10.11992/tis.202112038]
 ZHANG Mingquan,ZHOU Hui,CAO Jingang.Dual BERT directed sentiment text classification based on attention mechanism[J].CAAI Transactions on Intelligent Systems,2022,17():1220.[doi:10.11992/tis.202112038]
[7]胡文彬,陈龙,黄贤波,等.融合交叉注意力的突发事件多模态中文反讽识别模型[J].智能系统学报,2024,19(2):392.[doi:10.11992/tis.202212011]
 HU Wenbin,CHEN Long,HUANG Xianbo,et al.A multimodal Chinese sarcasm detection model for emergencies based on cross attention[J].CAAI Transactions on Intelligent Systems,2024,19():392.[doi:10.11992/tis.202212011]

备注/Memo

收稿日期:2017-06-08。
基金项目:国家自然科学基金项目(61672276);江苏省自然科学基金项目(20161406).
作者简介:吴钟强,男,1992年生,硕士研究生,主要研究方向为文本挖掘、情感分析;张耀文,男,1989年生,硕士研究生,主要研究方向为文本挖掘、情感分析;商琳,女,1973年生,副教授,博士,主要研究方向为计算智能、机器学习、文本挖掘等。
通讯作者:吴钟强.E-mail:wuzqchom@163.com

更新日期/Last Update: 2017-10-25
Copyright © 《 智能系统学报》 编辑部
地址:(150001)黑龙江省哈尔滨市南岗区南通大街145-1号楼 电话:0451- 82534001、82518134 邮箱:tis@vip.sina.com