[1] |
马晓玲, 金碧漪, 范并思 . 中文文本情感倾向分析研究[J]. 情报资料工作, 2013(1): 52-56.
|
|
MA X L , JIN B Y , FAN B S . An analysis of Chinese text emotional tendency[J]. Information and Documentation Services, 2013(1): 52-56.
|
[2] |
DAS S , CHEN M . Yahoo! for amazon:extracting market sentiment from stock message boards[R]. 2001.
|
[3] |
TURNEY P D , . Thumbs up or thumbs down?:semantic orientation applied to unsupervised classification of reviews[C]// Meeting on Association for Computational Linguistics,July 7-12,Philadelphia,Pennsylvania. New York:ACM Press, 2002: 417-424.
|
[4] |
MORAES R , VALIATI J F , NETO W P G ,et al. Document-level sentiment classification:an empirical comparison between SVM and ANN[J]. Expert Systems with Applications, 2013,40(2): 621-633.
|
[5] |
HADDI E , LIU X H , SHI Y . The role of text pre-processing in sentiment analysis[J]. Procedia Computer Science, 2013(17): 26-32.
|
[6] |
KANG H , YOO S J , HAN D . Senti-lexicon and improved Na?veBayes algorithms for sentiment analysis of restaurant reviews[J]. Expert Systems with Applications, 2012,39(5): 6000-6010.
|
[7] |
YU L C , WU J L , CHANG P C . Using a contextual entropy model to expand emotion words and their intensity for the sentiment classification of stock market news[J]. Knowledge-Based Systems, 2013(41): 89-97.
|
[8] |
高伟, 王中卿, 李寿山 . 基于集成学习的半监督情感分类方法研究[J]. 中文信息学报, 2013,27(3): 120-126.
|
|
GAO W , WANG Z Q , LI S S . Semi-supervised sentiment classification with a ensemble strategy[J]. Journal of Chinese Information Processing, 2013,27(3): 120-126.
|
[9] |
赵传君, 王素格, 李德玉 . 基于分组提升集成的跨领域文本情感分类[J]. 计算机研究与发展, 2015,52(3): 629-638.
|
|
ZHAO C J , WANG S G , LI D Y . Cross-domain text sentiment classification based on grouping-Adaboost ensemble[J]. Journal of Computer Research and Development, 2015,52(3): 629-638.
|
[10] |
张越兵, 苗夺谦, 张志飞 . 基于三支决策的多粒度文本情感分类模型[J]. 计算机科学, 2017,44(12): 188-193,215.
|
|
ZHANG Y B , MIAO D Q , ZHANG Z F . Multi-granularity text sentiment classification model based on three decision making[J]. Computer Science, 2017,44(12): 188-193,215.
|
[11] |
于海燕, 陈丽如, 郑文斌 . 基于核超限学习机的中文文本情感分类[J]. 中国计量学院学报, 2016,27(2): 228-233.
|
|
YU H Y , CHEN L R , ZHENG W B . Chinese text sentiment classification based on kernel extreme learning machines[J]. Journal of China Jiliang University, 2016,27(2): 228-233.
|
[12] |
朱宪莹, 刘箴, 金炜 ,等. 基于特征融合的层次结构微博情感分类[J]. 电信科学, 2016,32(7): 106-114.
|
|
ZHU X Y , LIU Z , JIN W ,et al. Hierarchical micro-blog sentiment classification based on feature fusion[J]. Telecommunications Science, 2016,32(7): 106-114.
|
[13] |
CATAL C , NANGIR M . A sentiment classification model based on multiple classifiers[J]. Applied Soft Computing, 2017(50): 135-141.
|
[14] |
ONAN A , KORUKO?LU S , BULUT H . A multiobjective weighted voting ensemble classifier based on differential evolution algorithm for text sentiment classification[M]. Oxford:Pergamon Press,Inc. 2016.
|
[15] |
杜慧, 徐学可, 伍大勇 . 基于情感词向量的微博情感分类[J]. 中文信息学报, 2017,31(3): 170-176.
|
|
DU H , XU X K , WU D Y . A sentiment classification method based on sentiment-specific word embedding[J]. Journal of Chinese Information Processing, 2017,31(3): 170-176.
|
[16] |
LIU Y , BI J W , FAN Z P . A method for multi-class sentiment classification based on an improved one-vs-one (OVO) strategy and the support vector machine (SVM) algorithm[J]. Information Sciences, 2017(394-395): 38-52.
|
[17] |
李然, 林政, 林海伦 . 文本情绪分析综述[J]. 计算机研究与发展, 2018,55(1): 30-52.
|
|
LI R , LIN Z , LIN H L . Summary of text sentiment analysis[J]. Journal of Computer Research and Development, 2018,55(1): 30-52.
|
[18] |
LIU S M , CHEN J H . A multi-label classification based approach for sentiment classification[J]. Expert Systems with Applications, 2015,42(3): 1083-1093.
|
[19] |
ZHANG X , LI W , LU S . Emotion detection in online social network based on multi-label learning[C]// 22nd International Conference on Database Systems for Advanced Applications,March 27-30,2017,Suzhou,China. Berlin:Springer, 2017: 659-674.
|
[20] |
LI J , RAO Y , JIN F ,et al. Multi-label maximum entropy model for social emotion classification over short text[J]. Neurocomputing, 2016(210): 247-256.
|