Adding redundant features for CRFs-based sentence sentiment classification

EMNLP 2008 - 2008 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference: A Meeting of SIGDAT, a Special Interest Group of the ACL

Volumn , Issue , 2008, Pages 117-126

  Zhao, Jun ^a   Liu, Kang ^a   Wang, Gen ^a  

^a INSTITUTE OF AUTOMATION   (China)

Author keywords

[No Author keywords available]

Indexed keywords

REDUNDANCY; SUPPORT VECTOR MACHINES;

CASCADED MODELS; CONTEXTUAL CONSTRAINTS; DIFFERENT LAYERS; ERROR PROPAGATION; REDUNDANT FEATURES; SENTIMENT CLASSIFICATION;

NATURAL LANGUAGE PROCESSING SYSTEMS;

EID: 74849096097     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3115/1613715.1613733     Document Type: Conference Paper

References (16)

1. Alina A. and Sabine B. 2008. When Specialists and Generalists Work Together: Overcoming Domain Dependence in Sentiment Tagging. In Proc. of ACL-08
2. Alistair Kennedy and Diana Inkpen. 2006. Sentiment Classification of Movie Reviews Using Contextual Valence Shifters. Computational Intelligence, 22(2), pages 110-125
3. Bo Pang, Lillian Lee and Shivakumar Vaithyanathan. 2002. Thumbs up? Sentiment classification using machine learning techniques. In Proceedings of EMNLP 2002, pp.79-86.
4. Bo Pang and Lillian Lee. 2004. A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts. In Proceedings of ACL 2004, pp.271-278.
5. Bo Pang and Lillian Lee. 2005. Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales. In Proceedings of ACL 2005, pp.115-124.
6. Ivan Titov and Ryan McDonald. 2008. A Joint Model o f Text and Aspect Ratings of Sentiment Summarization. In Proceedings of ACL-08, pages 308-316
7. Janyce Webie, Theresa Wilson and Claire Cardie. 2005. Annotating expressions of opinions and emotions in lauguage. Language Resources and Evaluation 2005
8. Fei Sha and Fernando Pereira, 2003 Shallow Parsing with Conditional Random Fields, In Proceedings ofHLT-NAACL 2003, Edmonton, Canada, pp. 213-220.
9. Kim, S and Edward H. Hovy. 2004. Determining the Sentiment of Opinions. In Proceedings of COLING-04.
10. Kamal Nigam, John Lafferty and Andrew McCallum. 1999. Using Maximum Entropy for Text Classification. In Proceedings of IJCAI Workshop on Machine Learning for Information Filtering, pages 61-67.
11. J Lafferty, A McCallum, F Pereira. 2001. Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In Proceedings of ICML-01, pages 282.289.
12. th ACM international conference on Information and knowledge management (CIKM), pages 43-50.
13. M. Hu and B. Liu. 2004a. Mining and summarizing customer reviews. In Proceedings of the 2004 ACM SIGKDD international conference on Knowledge discovery and data mining, pages 168-177.
14. Ryan McDonald, Kerry Hannan and Tyler Neylon et al. Structured Models for Fine-to-Coarse Sentiment Analysis. In Proceedings of ACL 2007, pp. 432-439.
15. Wei Wu, Zoubin Ghahraman, 2005. Gaussian Processes for Oridinal Regression. The Journal of Machine learning Research, 2005
16. Y. Mao and G. Lebanon, 2007. Isotonic Conditional Random Fields and Local Sentiment Flow. Advances in Neural Information Processing Systems 19, 2007