A walk-based semantically enriched tree kernel over distributed word representations

EMNLP 2013 - 2013 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference

Volumn , Issue , 2013, Pages 1411-1416

  Srivastava, Shashank ^a   Hovy, Dirk ^b   Hovy, Eduard ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

^b UNIVERSITY OF COPENHAGEN   (Denmark)

Author keywords

[No Author keywords available]

Indexed keywords

NATURAL LANGUAGE PROCESSING SYSTEMS; SEMANTICS;

CONTINUOUS SPACES; DISTRIBUTED REPRESENTATION; EFFICIENT FORMULATION; MATRIX OPERATIONS; SEMANTIC SIMILARITY; STATE OF THE ART; VECTOR REPRESENTATIONS; WORD REPRESENTATIONS;

FORESTRY;

LANGUAGES; WORD PROCESSING;

EID: 84906931485     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (25)

1. Sabri Boughorbel, Jean-Philippe Tarel, and Nozha Boujemaa. 2005. Conditionally positive definite kernels for svm based image recognition. In ICME, pages 113-116.
2. Jorge Carrillo de Albornoz, Laura Plaza, and Pablo Gervás. 2010. A hybrid approach to emotional sentence polarity and intensity classification. In Proceedings of the Fourteenth Conference on Computational Natural Language Learning, pages 153-161. Association for Computational Linguistics.
3. Michael Collins and Nigel Duffy. 2002. New ranking algorithms for parsing and tagging: Kernels over discrete structures, and the voted perceptron. In Proceedings of the 40th annual meeting on association for computational linguistics, pages 263-270. Association for Computational Linguistics.
4. Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen, Koray Kavukcuoglu, and Pavel Kuksa. 2011. Natural language processing (almost) from scratch. Journal of Machine Learning Research, 12:2493-2537.
5. Danilo Croce, Alessandro Moschitti, and Roberto Basili. 2011. Structured lexical similarity via convolution kernels on dependency trees. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, pages 1034-1046. Association for Computational Linguistics.
6. Chad Cumby and Dan Roth. 2003. On kernel methods for relational learning. In In Proc. of the International Conference on Machine Learning, pages 107-114.
7. Andrew Finch. 2005. Using machine translation evaluation techniques to determine sentence-level semantic equivalence. In In IWP2005.
8. Thomas Gartner, Peter Flach, and Stefan Wrobel. 2003. On graph kernels: Hardness results and efficient alternatives. In Proceedings of the Annual Conference on Computational Learning Theory, pages 129-143. Springer.
9. David Haussler. 1999. Convolution kernels on discrete structures. Technical Report Technical Report UCS-CRL-99-10, UC Santa Cruz.
10. Dirk Hovy, Shashank Srivastava, Sujay Kumar Jauhar, Mrinmaya Sachan, Kartik Goyal, Huiying Li, Whitney Sanders, and Eduard Hovy. 2013. Identifying metaphorical word use with tree kernels. In Proceedings of NAACL HLT, Meta4NLP Workshop.
11. Hisashi Kashima, Koji Tsuda, and Akihiro Inokuchi. 2003. Marginalized kernels between labeled graphs. In Proceedings of the Twentieth International Conference on Machine Learning, pages 321-328. AAAI Press.
12. Prodromos Malakasiotis. 2009. Paraphrase recognition using machine learning to combine similarity measures. In Proceedings of the ACL-IJCNLP 2009 Student Research Workshop, ACLstudent '09, pages 27-35, Stroudsburg, PA, USA. Association for Computational Linguistics.
13. Alessandro Moschitti, Daniele Pighin, and Roberto Basili. 2008. Tree kernels for semantic role labeling. Computational Linguistics, 34(2):193-224.
14. Alessandro Moschitti. 2004. A study on convolution kernels for shallow semantic parsing. In Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics, pages 335-es. Association for Computational Linguistics.
15. Alessandro Moschitti. 2006a. Efficient convolution kernels for dependency and constituent syntactic trees. In Machine Learning: ECML 2006, pages 318-329. Springer.
16. Alessandro Moschitti. 2006b. Making Tree Kernels Practical for Natural Language Learning. In In Proceedings of the 11th Conference of the European Chapter of the Association for Computational Linguistics.
17. Bo Pang and Lillian Lee. 2005. Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales. In Proceedings of the ACL.
18. Longhua Qian, Guodong Zhou, Fang Kong, Qiaoming Zhu, and Peide Qian. 2008. Exploiting constituent dependencies for tree kernel-based semantic relation extraction. In Proceedings of the 22nd International Conference on Computational Linguistics-Volume 1, pages 697-704. Association for Computational Linguistics.
19. Long Qiu, Min-Yen Kan, and Tat-Seng Chua. 2006. Paraphrase recognition via dissimilarity significance classification. In Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing, EMNLP '06, pages 18-26, Stroudsburg, PA, USA. Association for Computational Linguistics.
20. Chris Quirk, Chris Brockett, and William Dolan. 2004. Monolingual machine translation for paraphrase generation. In In Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing, pages 142-149.
21. Stephen Tratz and Eduard Hovy. 2011. A fast, accurate, non-projective, semantically-enriched parser. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, EMNLP '11, pages 1257-1268, Stroudsburg, PA, USA. Association for Computational Linguistics.
22. S. V. N. Vishwanathan and Alexander J. Smola. 2003. Fast kernels for string and tree matching. In Advances In Neural Information Processing Systems 15, pages 569-576. MIT Press.
23. S. V. N. Vishwanathan, Nicol N. Schraudolph, Risi Kondor, and Karsten M. Borgwardt. 2010. Graph kernels. J. Mach. Learn. Res., 99:1201-1242, August.
24. Xinglong Wang, Jun'ichi Tsujii, and Sophia Ananiadou. 2010. Disambiguating the species of biomedical named entities using natural language parsers. Bioinformatics, 26(5):661-667.
25. Yitao Zhang and Jon Patrick. 2005. Paraphrase identification by text canonicalization. In In Proceedings of the Australasian Language Technology Workshop 2005.