Efficient linearization of tree kernel functions

CoNLL 2009 - Proceedings of the Thirteenth Conference on Computational Natural Language Learning

Volumn , Issue , 2009, Pages 30-38

  Pighin, Daniele ^a   Moschitti, Alessandro ^b  

^a ITC IRST   (Italy)

^b UNIVERSITY OF TRENTO   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

FORESTRY; REVERSE ENGINEERING; SEMANTICS; SUPPORT VECTOR MACHINES; VECTOR SPACES; TREES (MATHEMATICS);

COMPUTATIONAL BURDEN; DATA SET; FEATURE SPACE; HIGH-DIMENSIONAL; IMPLICIT REPRESENTATION; LARGE DATASETS; SEMANTIC ROLE LABELING; TREE KERNELS; GENERALISATION; HIGHER-DIMENSIONAL; KERNEL FUNCTION; LINEARISATION; STRING KERNEL; SUPPORT VECTORS MACHINE;

TREES (MATHEMATICS); REVERSE ENGINEERING;

EID: 77958030821     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3115/1596374.1596383     Document Type: Conference Paper

References (33)

1. Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti, and Alessandro Moschitti. 2006. Fast on-line kernel learning for trees. In Proceedings of ICDM'06.
2. Nicola Cancedda, Eric Gaussier, Cyril Goutte, and Jean Michel Renders. 2003. Word sequence kernels. Journal of Machine Learning Research, 3:1059-1082.
3. Xavier Carreras and Lluís Màrquez. 2005. Introduction to the CoNLL-2005 Shared Task: Semantic Role Labeling. In Proceedings of CoNLL'05.
4. Eugene Charniak. 2000. A maximum-entropy-inspired parser. In Proceedings of NAACL'00.
5. Michael Collins and Nigel Duffy. 2002. New Ranking Algorithms for Parsing and Tagging: Kernels over Discrete Structures, and the Voted Perceptron. In Proceedings of ACL'02.
6. Aron Culotta and Jeffrey Sorensen. 2004. Dependency Tree Kernels for Relation Extraction. In Proceedings of ACL'04.
7. Chad Cumby and Dan Roth. 2003. Kernel Methods for Relational Learning. In Proceedings of ICML 2003.
8. Hal Daumé III and Daniel Marcu. 2004. Np bracketing by maximum entropy tagging and SVM reranking. In Proceedings of EMNLP'04.
9. Daniel Gildea and Daniel Jurafsky. 2002. Automatic labeling of semantic roles. Computational Linguistics, 28:245-288.
10. Hans P. Graf, Eric Cosatto, Leon Bottou, Igor Durdanovic, and Vladimir Vapnik. 2004. Parallel support vector machines: The cascade svm. In Neural Information Processing Systems.
11. Isabelle Guyon and André Elisseeff. 2003. An introduction to variable and feature selection. Journal of Machine Learning Research, 3:1157-1182.
12. David Haussler. 1999. Convolution kernels on discrete structures. Technical report, Dept. of Computer Science, University of California at Santa Cruz.
13. T. Joachims. 2000. Estimating the generalization performance of a SVM efficiently. In Proceedings of ICML'00.
14. Hisashi Kashima and Teruo Koyanagi. 2002. Kernels for semi-structured data. In Proceedings of ICML'02.
15. Jun'ichi Kazama and Kentaro Torisawa. 2005. Speeding up training with tree kernels for node relation labeling. In Proceedings of HLT-EMNLP'05.
16. Taku Kudo and Yuji Matsumoto. 2003. Fast methods for kernel-based text analysis. In Proceedings of ACL'03.
17. Taku Kudo, Jun Suzuki, and Hideki Isozaki. 2005. Boosting-based parse reranking with subtree features. In Proceedings of ACL'05.
18. Alessandro Moschitti and Cosmin Bejan. 2004. A semantic kernel for predicate argument classification. In CoNLL-2004, Boston, MA, USA.
19. Alessandro Moschitti, Daniele Pighin, and Roberto Basili. 2006. Semantic role labeling via tree kernel joint inference. In Proceedings of CoNLL-X, New York City.
20. Alessandro Moschitti, Daniele Pighin, and Roberto Basili. 2008. Tree kernels for semantic role labeling. Computational Linguistics, 34(2):193-224.
21. Alessandro Moschitti. 2006. Making tree kernels practical for natural language learning. In Proccedings of EACL'06.
22. Julia Neumann, Christoph Schnorr, and Gabriele Steidl. 2005. Combined SVM-Based Feature Selection and Classification. Machine Learning, 61(1-3):129-150.
23. Martha Palmer, Daniel Gildea, and Paul Kingsbury. 2005. The proposition bank: An annotated corpus of semantic roles. Comput. Linguist., 31(1):71-106.
24. J. Pei, J. Han, Mortazavi B. Asl, H. Pinto, Q. Chen, U. Dayal, and M. C. Hsu. 2001. PrefixSpan Mining Sequential Patterns Efficiently by Prefix Projected Pattern Growth. In Proceedings of ICDE'01.
25. Alain Rakotomamonjy. 2003. Variable selection using SVM based criteria. Journal of Machine Learning Research, 3:1357-1370.
26. Libin Shen, Anoop Sarkar, and Aravind k. Joshi. 2003. Using LTAG Based Features in Parse Reranking. In Proceedings of EMNLP'06.
27. Jun Suzuki and Hideki Isozaki. 2005. Sequence and Tree Kernels with Statistical Feature Mining. In Proceedings of the 19th Annual Conference on Neural Information Processing Systems (NIPS'05).
28. Ivan Titov and James Henderson. 2006. Porting statistical parsers with data-defined kernels. In Proceedings of CoNLL-X.
29. Kristina Toutanova, Penka Markova, and Christopher Manning. 2004. The Leaf Path Projection View of Parse Trees: Exploring String Kernels for HPSG Parse Selection. In Proceedings of EMNLP 2004.
30. Vladimir N. Vapnik. 1998. Statistical Learning Theory. Wiley-Interscience.
31. Jason Weston, Sayan Mukherjee, Olivier Chapelle, Massimiliano Pontil, Tomaso Poggio, and Vladimir Vapnik. 2001. Feature Selection for SVMs. In Proceedings of NIPS'01.
32. Jason Weston, André Elisseeff, Bernhard Schölkopf, and Mike Tipping. 2003. Use of the zero norm with linear models and kernel methods. J. Mach. Learn. Res., 3:1439-1461.
33. Mohammed J Zaki. 2002. Efficiently mining frequent trees in a forest. In Proceedings of KDD'02.