Analysis of three methods for web-based opinion mining

ICMLC（2011）

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摘要

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.

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关键词

measuring semantic orientation,semantic pattern,svm text classification method,weighted sentiment lexicon,document,semantic orientation,text classification,knn,web-based opinion mining,internet,natural language processing,semantic feature word,opinion mining tool,data mining,classification,text analysis,support vector machines,natural language syntax,support vector machine,machine learning,opinion mining,algorithm design and analysis,natural language,algorithm design,feature extraction,pattern matching,semantics

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