模式识别与人工智能
Tuesday, Jan. 14, 2025 Home      About Journal      Editorial Board      Instructions      Ethics Statement      Contact Us                   中文
  2016, Vol. 29 Issue (4): 289-297    DOI: 10.16451/j.cnki.issn1003-6059.201604001
Papers and Reports Current Issue| Next Issue| Archive| Adv Search |
A Semi-supervised Method for Phrase-Level Sentiment Analysis
Odbal, WANG Zengfu
Nuclear Environment Telerobot Laboratory, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031
Department of Automation, University of Science and Technology of China, Hefei 230027

Download: PDF (487 KB)   HTML (1 KB) 
Export: BibTeX | EndNote (RIS)      
Abstract  The existing methods for sentiment analysis can not dig more complex linguistic phenomena in emotional expression and they encounter the challenge of sparse features. An innovative semi-supervised phrase-level sentiment analysis method based on semantic space model is proposed. Firstly, the problem of word representation in semantic space is discussed and word-level semantic distribution computing methods based on dependency grammar semantic space model are proposed, and the computational procedure is completed by using unsupervised method. Secondly, the problems of phrase recognition and representation are discussed and nonlinear combinations of word-level semantic distribution are used to represent the multi-word structures. Finally, a neutral network algorithm is used to design the phrase-level sentiment analysis system based on word level semantic distribution and phrasal structure representation. Experimental results on real Chinese corpora show the expected recognition accuracy of the model.
Key wordsSentiment Analysis      Word Representation      Phrase-Level Composition      Neural Network     
Received: 10 September 2015     
ZTFLH: TP 391  
Fund:Supported by National Natural Science Foundation of China (No.61472393)
About author:: (Odbal(Corresponding author), born in 1981, master, assistant professor. Her research interests include natural language processing, affective computing, artificial intelligence and pa-ttern recognition.)
(WANG Zengfu, born in 1960, Ph.D., professor. His research interests include stereo vision, biometrics, affective computing and intelligent robot.)
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors
Odbal
WANG Zengfu
Cite this article:   
Odbal,WANG Zengfu. A Semi-supervised Method for Phrase-Level Sentiment Analysis[J]. , 2016, 29(4): 289-297.
URL:  
http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201604001      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2016/V29/I4/289
Copyright © 2010 Editorial Office of Pattern Recognition and Artificial Intelligence
Address: No.350 Shushanhu Road, Hefei, Anhui Province, P.R. China Tel: 0551-65591176 Fax:0551-65591176 Email: bjb@iim.ac.cn
Supported by Beijing Magtech  Email:support@magtech.com.cn