Computer Science ›› 2020, Vol. 47 ›› Issue (11): 275-279.doi: 10.11896/jsjkx.191000174
• Artificial Intelligence • Previous Articles Next Articles
MA Xiao-hui1, JIA Jun-zhi2, ZHOU Xiang-zhen3, YAN Jun-ya1
CLC Number:
[1] CAMBRIA E,PORIA S,GELBUKH A,et al.Sentiment Analysis Is a Big Suitcase[J].IEEE Intelligent Systems,2017,32(6):74-80. [2] LIU B.Sentiment Analysis:Mining Opinions,Sentiments,andEmotions[M].Cambridge University Press,2015:7-8. [3] TABOADA M,BROOKE J,TOFILOSKI M,et al.Lexicon-based methods for sentiment analysis[J].Computational Linguistics,2011,37(2):267-307. [4] CAMBRIA E,SCHULLER B,XIA Y,et al.New avenues inopinion mining and sentiment analysis[J].IEEE Intelligent Systems,2013,28(2):15-21. [5] DING X,LIU B,YU P S.A holistic lexicon-based approach toopinion mining[C]//Proceedings of the 2008International Conference on Web Search and Data Mining.Palo Alto:ACM,2008:231-240. [6] LE Q,MIKOLOV T.Distributed representations of sentencesand documents[C]//Proceedings of the 31st International Conference on Machine Learning.Beijing:JMLR,2014:1188-1196. [7] ALPAYDIN E.Introduction to Machine Learning[M].London:MIT press,2014:127-130. [8] GAO M Z.Research on Sentiment Classification and OpinionMining Technique of Online Reviews[D].Changsha:National University of Defense Technology,2014. [9] KAMPS J,MARX M,MOKKEN R J,et al.Using Wordnet to Measure Semantic Orientation of Adjectives[C]//Proceedings of the Fourth International Conference on Language Resources and Evaluation.Lisbon:ELRA,2004:1115-1118. [10] GUERINI M,LORENZO G,MARCO T.Sentiment Analysis:How to Derive Prior Polarities from Sentiwordnet[C]//Proceedings of the 2013 Conference of Empirical Methods on Natural Language Processing.Washington:Association for Computational Linguistics,2013:1259-1269. [11] LI C J.Text sentiment polarity analysis based on Chinese reviews in hotel domain[D].Guangzhou:South China University of Technology,2016. [12] HAMILTON W L,CLARK K,LESKOVEC J,et al.Inducingdomain-specific sentiment lexicons from unlabeled corpora[C]//Proceedings of the Conference on Empirical Methods in Natural Language Processing.Austin:Association for Computational Linguistics,2016:595-605. [13] LUO S L,MAO Y Y,PAN L M,et al.A Method of Text Sentiment Classification by Extending Semantic Similar Sentiment Words[J].Transactions of Beijing Institute of Technology,2018,38(11):1156-1162,1176. [14] ZHU G,IGLESIAS C A.Computing semantic similarity of concepts in knowledge graphs[J].IEEE Transactions on Knowledge and Data Engineering,2017,29(1):72-85. [15] GLIGOROV R,TEN KATE W,ALEKSOVSKI Z,et al.Using google distance to weight approximate ontology matches[C]//Proceedings of the 16th International Conference on World Wide Web.New York:ACM,2007:767-776. [16] MIKOLOV T,CORRADO G,CHEN K,et al.Efficient Estimation of Word Representations in Vector Space[C]//Proceedings of the International Conference on Learning Representations.2013:1-12. [17] BUDANITSKY A,HIRST G.Evaluating wordnet-based measures of lexical semantic relatedness[J].Computational Linguistics,2006,32(1):13-47. [18] BENGIO Y,DUCHARME R,VINCENT P.A Neural Probabilistic Language Model[J].Journal of Machine Learning Research,2003,3:1137-1155. [19] GOLDBERG Y.A Primer on Neural Network Models for Natural Language Processing[J].Journal of Artificial Intelligence Research,2016,57:345-420. [20] WANG Y,TAO Y Z,ZHANG Q.Research on sentiment orientation of product feature from Chinese reviews on the internet[J].Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition),2017,29(1):75-83. [21] YANG W,SONG J J,TANG J Q. A Study on the Classification Approach for Chinese MicroBlog Subjective and Objective Sentences [J].Journal of Chongqing University of Technology(Natural Science),2013,27(1):51-56. [22] PORIA S,CAMBRIA E,GELBUKH A.Aspect Extraction for Opinion Mining with a Deep Convolutional Neural Network[J].Knowledge-Based Systems,2016,108:42-49. [23] SCHNABEL T,LABUTOV I,MIMNO D,et al.Evaluationmethods for unsupervised word embeddings[C]//Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing.Lisbon:Association for Computational Linguistics,2015:298-307. [24] ARAQUE O,CORCUERA-PLATAS I,SÁNCHEZ-RADA J F,et al.Enhancing deep learning sentiment analysis with ensemble techniques in social applications[J].Expert Systems with Applications,2017,77:236-246. [25] DAI A M,LE Q V.Semi-supervised sequence learning[C]//Proceedings of the 28th International Conference on Neural Information Processing Systems.Montreal:MIT Press Cambridge,2015:3079-3087. [26] KIM Y.Convolutional neural networks for sentence classification[C]//Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing.Doha:Association for Computational Linguistics,2014:1746-1751. [27] RUDER S,GHAFFARI P,BRESLIN J G.INSIGHT-1 at Se-mEval-2016 Task 5:Deep Learning for Multilingual Aspect-based Sentiment Analysis[C]//Proceedings of SemEval-2016.San Diego:2016 Association for Computational Linguistics,2016:330-336. [28] TANG D,WEI F,QIN B,et al.Sentiment embeddings with applications to sentiment analysis[J].IEEE Transactions on Knowledge and Data Engineering,2016,28(2):496-509. [29] YU S W,LU Q,CHEN W L.Fine-grained Opinion MiningBased on Feature Representation of Domain Sentiment Lexicon[J].Journal of Chinese Information Processing,2019,33(2):112-121. |
[1] | LI Bin, WAN Yuan. Unsupervised Multi-view Feature Selection Based on Similarity Matrix Learning and Matrix Alignment [J]. Computer Science, 2022, 49(8): 86-96. |
[2] | HU Yan-yu, ZHAO Long, DONG Xiang-jun. Two-stage Deep Feature Selection Extraction Algorithm for Cancer Classification [J]. Computer Science, 2022, 49(7): 73-78. |
[3] | ZENG Zhi-xian, CAO Jian-jun, WENG Nian-feng, JIANG Guo-quan, XU Bin. Fine-grained Semantic Association Video-Text Cross-modal Entity Resolution Based on Attention Mechanism [J]. Computer Science, 2022, 49(7): 106-112. |
[4] | HOU Yu-tao, ABULIZI Abudukelimu, ABUDUKELIMU Halidanmu. Advances in Chinese Pre-training Models [J]. Computer Science, 2022, 49(7): 148-163. |
[5] | KANG Yan, WANG Hai-ning, TAO Liu, YANG Hai-xiao, YANG Xue-kun, WANG Fei, LI Hao. Hybrid Improved Flower Pollination Algorithm and Gray Wolf Algorithm for Feature Selection [J]. Computer Science, 2022, 49(6A): 125-132. |
[6] | LIN Xi, CHEN Zi-zhuo, WANG Zhong-qing. Aspect-level Sentiment Classification Based on Imbalanced Data and Ensemble Learning [J]. Computer Science, 2022, 49(6A): 144-149. |
[7] | HAN Hong-qi, RAN Ya-xin, ZHANG Yun-liang, GUI Jie, GAO Xiong, YI Meng-lin. Study on Cross-media Information Retrieval Based on Common Subspace Classification Learning [J]. Computer Science, 2022, 49(5): 33-42. |
[8] | CHU An-qi, DING Zhi-jun. Application of Gray Wolf Optimization Algorithm on Synchronous Processing of Sample Equalization and Feature Selection in Credit Evaluation [J]. Computer Science, 2022, 49(4): 134-139. |
[9] | SUN Lin, HUANG Miao-miao, XU Jiu-cheng. Weak Label Feature Selection Method Based on Neighborhood Rough Sets and Relief [J]. Computer Science, 2022, 49(4): 152-160. |
[10] | PAN Zhi-hao, ZENG Bi, LIAO Wen-xiong, WEI Peng-fei, WEN Song. Interactive Attention Graph Convolutional Networks for Aspect-based Sentiment Classification [J]. Computer Science, 2022, 49(3): 294-300. |
[11] | LI Zong-ran, CHEN XIU-Hong, LU Yun, SHAO Zheng-yi. Robust Joint Sparse Uncorrelated Regression [J]. Computer Science, 2022, 49(2): 191-197. |
[12] | LI Yu-qiang, ZHANG Wei-jiang, HUANG Yu, LI Lin, LIU Ai-hua. Improved Topic Sentiment Model with Word Embedding Based on Gaussian Distribution [J]. Computer Science, 2022, 49(2): 256-264. |
[13] | LIU Kai, ZHANG Hong-jun, CHEN Fei-qiong. Name Entity Recognition for Military Based on Domain Adaptive Embedding [J]. Computer Science, 2022, 49(1): 292-297. |
[14] | LI Zhao-qi, LI Ta. Query-by-Example with Acoustic Word Embeddings Using wav2vec Pretraining [J]. Computer Science, 2022, 49(1): 59-64. |
[15] | ZHANG Ye, LI Zhi-hua, WANG Chang-jie. Kernel Density Estimation-based Lightweight IoT Anomaly Traffic Detection Method [J]. Computer Science, 2021, 48(9): 337-344. |
|