[1] 敦欣卉,张云秋,杨铠西. 基于微博的细粒度情感分析[J]. 数据分析与知识发现,2017, 001(007):61-72.
Dun X, Zhang Y, Yang K. Fine-grained
Sentiment Analysis Based on Microblog[J]. Data Analysis
and Knowledge Discovery, 2017, 001(007): 61-72.
[2] Zhao J, Dong
L, Wu J, et al. MoodLens: An emoticon-based sentiment analysis system for chinese tweets. ACM, 2012.
[3] Wang H, Can
D, Kazemzadeh A, et al. A System for Real-time Twitter Sentiment Analysis of 2012 U.S. Presidential Election
Cycle[C]// Acl System Demonstrations. 2012.
[4] Williams J,
Katz G. Extracting and modeling durations for habits and events from
Twitter[C]// Meeting of the
Association for Computational Linguistics: Short Papers. 2013.
[5] 李忠俊. 基于话题检测与聚类的内部舆情监测系统[J]. 计算机科学,2012,39(012):237-240.
LI Z J. Internal Public Opinion Monitoring System Based on Topic
Detection and Clustering [J]. Computer
Science, 2012, 39(012): 237-240.
[6] Yi J,
Nasukawa T, Bunescu R, et al. Sentiment analyzer: extracting sentiments about a
given topic using natural language
processing techniques[C]// Third IEEE International Conference on Data Mining. IEEE, 2003.
[7] Riloff E M,
Shepherd J. A Corpus-Based Approach for Building Semantic Lexicons[J]. 1997.
[8] 熊德兰,程菊明,田胜利. 基于HowNet的句子褒贬倾向性研究[J]. 计算机工程与应用, 2008,(22):143-145.
Xiong D, Cheng J, Tian Shengli. A Study of Sentence Praisal and Derogation Tendency
Based on HowNet [J]. Computer
Engineering and Applications, 2008, (22): 143-145.
[9] 潘明慧,牛耘. 基于多线索混合词典的微博情绪识别[J]. 计算机技术与发展,2014,(9): 28-32.
Pan M H, Niu Y. Microblog Emotion
Recognition Based on Multi-cue Hybrid Dictionary [J]. Computer
Technology and Development, 2014, (9): 28-32.
[10] Pang B. Thumbs up Sentiment Classification Using
Machine Learning Techniques[J]. Proc. EMNLP,
Philadelphia. PA, USA, 2002.
[11] 杨艳霞. 基于分类的微博情感分析算法研究及实现[J]. 计算机与数字工程,2017,45(2): 197-197.
Yang Y X. Microblog Sentiment Analysis Algorithm Research and
Implementation Based on Classification
[J]. Computer & Digital Engineering, 2017, 45(2): 197-200.
[12] COLLOBERT R, WESTON J, BOTTOU L, et al. Natural
language processing(almost)from scratch[J].
The Journal of Machine Learning Research, 2011, 12:2493-2537.
[13] Al-Rifaie M
M, Bishop J M. Swarmic Sketches and Attention Mechanism[J]. Springer, Berlin, Heidelberg, 2013, 85–96,.
[14] Mousa E D, Vryniotis V. Sentiment analysis and
opinion mining: on optimal parameters and performances[M].
John Wiley & Sons, Inc. 2015.
[15] 宋婷,陈战伟,杨海峰. 基于分层注意力网络的方面情感分析[J]. 大数据,2020,6(5):10.
Ting SONG, Zhanwei CHEN, Haifeng YANG. Aspect sentiment analysis based on
a hierarchical attention
network[J]. Big Data Research, 2020, 6(5): 10.
[16] 徐志栋,陈炳阳,王晓,等.基于胶囊网络的方面级情感分类研究[J]. 智能科学与技术学报,2020,2(3):284-292.
XU Z D, CHEN B Y, WANG X, et al. Research on capsule network-based for
aspect-level sentiment classification[J]. Chinese Journal of Intelligent
Science and Technology, 2020, 2(3): 284-292.
[17] 张宝华,张华平,厉铁帅,等.基于多输入模型及句法结构的中文评论情感分析方法[J]. 大数据,2021,7(6):41-52.
ZHANG B H, ZHANG H P, LI T S, et al. Chinese comment
sentiment analysis method based on multi-input
model and syntactic structure[J]. Big Data Research, 2021, 7(6): 41-52.
[18] Radford A,
Narasimhan K, Salimans T, et al. Improving language understanding by generative
pre-training[J]. 2018.
[19] Devlin J, Chang M W, Lee K, et al. BERT:
Pre-training of Deep Bidirectional Transformers for Language Understanding[J]. 2018.
[20] Vaswani A, Shazeer N, Parmar N, et al. Attention is all
you need[C]. Advances in neural information processing systems, 2017, 30.
[21] Sun C, Qiu X, Xu Y, et al. How to Fine-Tune BERT for
Text Classification[J]. Springer, Cham, 2019.
[22] 杨晨,宋晓宁,宋威. SentiBERT:结合情感信息的预训练语言模型[J]. 计算机科学与探索, 2020, 14(9):8.
Chen Y, Xiaoning S, Wei S.
SentiBERT: Pre-training Language Model Combining Sentiment Information[J].
Journal of Frontiers of Computer Science & Technology, 2020, 14(9): 8.
|