Name
Abstract | ||
|---|---|---|
This paper presents a combined method of syntactic structure, dependency relation and SVM classifier to extract opinion sentences. At first, we use the syntactic structure templates with high confidence summarized artificially and the dependency relation templates with high precision obtained by a dependency relation extraction algorithm to tag sentences as opinion sentence. Then we input the remaining test data to a trained SVM classifier which is created by a rigorous process of feature selection. Eventually the combined method performed well, achieving 92.6% recall with 85.5% precision. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/NLPKE.2010.5587835 | NLPKE |
Keywords | Field | DocType |
dependency relation extraction algorithm,pattern classification,svm classifier,svm,syntactic structure,syntactic structure templates,opinion sentence,template,feature selection,dependency relation,text analysis,sentences tagging,support vector machines,opinion sentences extraction,relation extraction | Dependency relation,Feature selection,Pattern recognition,Computer science,Support vector machine,Test data,Natural language processing,Artificial intelligence,Svm classifier,Template,Sentence,Syntax | Conference |
Volume | Issue | ISSN |
null | null | null |
ISBN | Citations | PageRank |
978-1-4244-6896-6 | 0 | 0.34 |
References | Authors | |
5 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhang Bo | 1 | 43 | 7.59 |
| Yanquan Zhou | 2 | 7 | 4.87 |
| Yu Mao | 3 | 0 | 0.34 |