[1] SUN C,HUANG L,QIU X. Utilizing BERT for aspect-based sentiment analysis via constructing auxiliary sentence[C]//Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics:Human Language Technologies. Stroudsburg, PA:Association for Computational Linguistics,2019:380-385. [2] LIU B. Sentiment Analysis and Opinion Mining[M]. Synthesis Lectures on Human Language Technologies. San Rafael, CA:Morgan and Claypool Publishers,2012:1-167. [3] 陈苹, 冯林. 情感分析中的方面提取综述[J]. 计算机应用, 2018,38(S2):84-88,96.(CHEN P,FENG L. Review of aspect extraction in sentiment analysis[J]. Journal of Computer Applications,2018,38(S2):84-88,96.) [4] PONTIKI M,GALANIS D,PAPAGEORGIOU H,et al. SemEval-2016 Task 5:aspect based sentiment analysis[C]//Proceedings of the 10th International Workshop on Semantic Evaluation. Stroudsburg, PA:Association for Computational Linguistics, 2016:19-30. [5] PONTIKI M,GALANIS D,PAPAGEORGIOU H,et al. SemEval-2015 task 12:aspect based sentiment analysis[C]//Proceedings of the 9th International Workshop on Semantic Evaluation. Stroudsburg, PA:Association for Computational Linguistics, 2015:486-495. [6] WAGNER J,ARORA P,CORTES S,et al. DCU:aspect-based polarity classification for SemEval Task 4[C]//Proceedings of the 8th International Workshop on Semantic Evaluation. Stroudsburg, PA:Association for Computational Linguistics,2014:223-229. [7] KIRITCHENKO S,ZHU X,CHERRY C,et al. NRC-Canada-2014:detecting aspects and sentiment in customer reviews[C]//Proceedings of the 8th International Workshop on Semantic Evaluation. Stroudsburg, PA:Association for Computational Linguistics,2014:437-442. [8] WANG Y,HUANG M,ZHU X,et al. Attention-based LSTM for aspect-level sentiment classification[C]//Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA:Association for Computational Linguistics, 2016:606-615. [9] MA D,LI S,ZHANG X,et al. Interactive attention networks for aspect-level sentiment classification[C]//Proceedings of the 26th International Joint Conferences on Artificial Intelligence. Palo Alto, CA:AAAI Press,2017:4068-4074. [10] HUANG B, OU Y, CARLEY K M. Aspect level sentiment classification with attention-over-attention neural networks[C]//Proceedings of the 2018 International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation, LNCS 10899. Cham:Springer,2018:197-206. [11] XUE W, LI T. Aspect based sentiment analysis with gated convolutional networks[C]//Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics. Stroudsburg, PA:Association for Computational Linguistics, 2018:2514-2523. [12] HOCHREITER S,SCHMIDHUBER J. Long short-term memory[J]. Neural Computation,1997,9(8):1735-1780. [13] PATTANAYAK S. Convolutional neural networks[M]. Pro Deep Learning with TensorFlow. Berkeley, CA:Apress, 2017:153-221. [14] DAUPHIN Y N,FAN A,AULI M,et al. Language modeling with gated convolutional networks[C]//Proceedings of the 34th International Conference on Machine Learning. New York:JMLR. org,2017:933-941. [15] CHEN Z,QIAN T. Transfer capsule network for aspect level sentiment classification[C]//Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Stroudsburg, PA:Association for Computational Linguistics, 2019:547-556. [16] DEVLIN J,CHANG M,LEE K,et al. BERT:pre-training of deep bidirectional transformers for language understanding[C]//. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics:Human Language Technologies. Stroudsburg,PA:Association for Computational Linguistics,2019:4171-4186. [17] VASWANI A,SHAZEER N,PARMAR N,et al. Attention is all you need[C]//Proceedings of the 31st International Conference on Neural Information Processing Systems. Red Hook,NY:Curran Associates Inc.,2017:6000-6010. [18] TENNEY I,DAS D,PAVLICK E. BERT rediscovers the classical NLP pipeline[C]//Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Stroudsburg, PA:Association for Computational Linguistics,2019:4593-4601. [19] GAO Z,FENG A,SONG X,et al. Target-dependent sentiment classification with BERT[J]. IEEE Access,2019,7:154290-154299. [20] 袁丁, 章剑林, 吴广建. 基于方面级的餐厅用户评论细粒度情感分析[J]. 软件,2019,40(8):181-189.(YUAN D,ZHANG J L,WU G J. Fine-particle sentiment analysis based on aspect level restaurant customer comment[J]. Computer Engineering and Software,2019,40(8):181-189.) [21] MIKOLOV T,CHEN K,CORRADO G,et al. Efficient estimation of word representations in vector space[EB/OL].[2019-11-12]. https://arxiv.org/pdf/1301.3781.pdf. [22] MIKOLOV T, SUTSKEVER I, CHEN K, et al. Distributed representations of words and phrases and their compositionality[C]//Proceedings of the 26th International Conference on Neural Information Processing Systems. New York, NY:Curran Associates Inc.,2013:3111-3119. [23] NYPASZKE A, GROSS S, MASSA F, et al. PyTorch:an imperative style,high-performance deep learning library[C]//Proceedings of the 33rd International Conference on Neural Information Processing Systems. New York, NY:Curran Associates Inc.,2019:8024-8035. [24] KRIZHEVSKY A,SUTSKEVER I,HINTON G E. ImageNet classification with deep convolutional neural networks[C]//Proceedings of the 25th International Conference on Neural Information Processing Systems. Red Hook, NY:Curran Associates Inc.,2012:1097-1105. |