DocumentCode :
3273964
Title :
Analysis of three methods for web-based opinion mining
Author :
Ma, Hai-bing ; Geng, Yi-bing ; Qiu, Jun-rui
Author_Institution :
Dept. of Political Work, Armed Police Force Political Acad. of Shanghai, Shanghai, China
Volume :
2
fYear :
2011
fDate :
10-13 July 2011
Firstpage :
915
Lastpage :
919
Abstract :
For the purpose of measuring semantic orientation of documents, we implemented an opinion mining tool which hybrids three different methods: The first one is based on semantic patterns, which simplify the structure of the natural language syntax; the second is based on the weighted sentiment lexicon, which used as semantic feature words; and the third one is based on traditional KNN or SVM text classification method. Our experiments show that each method has its own shorts and advantages.
Keywords :
Internet; classification; data mining; natural language processing; support vector machines; text analysis; KNN; SVM text classification method; Web-based opinion mining; document; measuring semantic orientation; natural language syntax; opinion mining tool; semantic feature word; semantic pattern; weighted sentiment lexicon; Algorithm design and analysis; Feature extraction; Machine learning; Pattern matching; Semantics; Support vector machines; Text categorization; Natural language processing; semantic orientation; text classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2011 International Conference on
Conference_Location :
Guilin
ISSN :
2160-133X
Print_ISBN :
978-1-4577-0305-8
Type :
conf
DOI :
10.1109/ICMLC.2011.6016768
Filename :
6016768
Link To Document :
بازگشت