원문정보
보안공학연구지원센터(IJHIT)
International Journal of Hybrid Information Technology
Vol.8 No.3
2015.03
pp.347-354
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
This paper studies the problem of extracting Chinese comparative sentences from user reviews, which is a problem of text classification in the level of sentence. This paper first deals with the class skewed problem of review data, and then builds a SVM (support vector machine) model to classify comparative and non-comparative sentences into different groups on a balanced dataset. Various linguistic and statistical features are introduced to characterize a sentence. Experiments were conducted on user-generated product reviews. As a result, our experiments show significant performance, an overall F-score of 85.87%.
목차
Abstract
1. Introduction
2. Related Work
3. Balancing of Corpus
3.1. Sentence Types
3.2. Data Balance Strategy
4. Extracting Comparative Sentences in Balanced Corpus
4.1. Mining Sequence Pattern Features
4.2. Manual Rule Features
5. Experimental Results
5.1. Data Sets
5.2. Experimental Results
6. Conclusion
Acknowledgement
References
1. Introduction
2. Related Work
3. Balancing of Corpus
3.1. Sentence Types
3.2. Data Balance Strategy
4. Extracting Comparative Sentences in Balanced Corpus
4.1. Mining Sequence Pattern Features
4.2. Manual Rule Features
5. Experimental Results
5.1. Data Sets
5.2. Experimental Results
6. Conclusion
Acknowledgement
References
저자정보
참고문헌
자료제공 : 네이버학술정보