Fine-Grained Sentiment Analysis Based on Sentiment Disambiguation
| Autor: | Xiao-Hong Cai, Pei-Yu Liu, Zhen-Fang Zhu, Zhi-Hao Wang |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Apriori algorithm
Information retrieval Polarity (physics) Computer science business.industry InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL Sentiment analysis Context (language use) 010103 numerical & computational mathematics 010502 geochemistry & geophysics Object (computer science) computer.software_genre Lexicon ComputingMethodologies_ARTIFICIALINTELLIGENCE 01 natural sciences Artificial intelligence InformationSystems_MISCELLANEOUS 0101 mathematics CRFS business computer Natural language processing Word (computer architecture) 0105 earth and related environmental sciences |
| Zdroj: | 2016 8th International Conference on Information Technology in Medicine and Education (ITME). |
| DOI: | 10.1109/itme.2016.0132 |
| Popis: | In this paper research on the problem of dynamic polarity change in review analysis. Firstly, Apriori algorithm is used to expand the sentiment ambiguous words based on context, and construct the sentiment ambiguous lexicon, namely triples of (sentiment object, sentiment word, sentiment polarity). Then make use of the condition random field model (CRFs) extracted emotional elements from comments, to fine-grained sentiment orientation analysis based on the sentiment ambiguous lexicon. Experimental results over product corpus in mobile-phone and computer domains show that the feasibility of the proposed method, and helps improve the accuracy of sentiment analysis. |
| Databáze: | OpenAIRE |
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