Locality-convolution kernel and its application to dependency parse ranking

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4031 LNAI, Issue , 2006, Pages 610-618

  Tsivtsivadze, Evgeni ^a   Pahikkala, Tapio ^a   Boberg, Jorma ^a   Salakoski, Tapio ^a  

^a TURKU CENTRE FOR COMPUTER SCIENCE   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTATIONAL METHODS; DATABASE SYSTEMS; FEATURE EXTRACTION; PATTERN MATCHING;

DEPENDENCY PARSE RANKING; KERNEL VALUE; LOCALITY-CONVOLUTION KERNEL; PARSE RANKING PERFORMANCE; REGULARIZED LEAST-SQUARES (RLS) ALGORITHM;

COMPUTER SCIENCE;

EID: 33746210706     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11779568_66     Document Type: Conference Paper

References (16)

1. Shawe-Taylor, J., Cristianini, N.: Kernel Methods for Pattern Analysis. Cambridge University Press, New York, NY, USA (2004)
2. Scholkopf, B., Smola, A.J.: Learning with Kernels: Support Vector Machines, Regularizatlon, Optimization, and Beyond. MIT Press, Cambridge, MA, USA (2001)
3. Collins, M., Duffy, N.: Convolution kernels for natural language. In Dietterich, T.G., Becker, S., Ghahramani, Z., eds.: NIPS, MIT Press (2001) 626-632
4. Suzuki, J., Hirao, T., Sasaki, Y., Maeda, E.: Hierarchical directed acyclic graph kernel: Methods for structured natural language data. In: ACL, (2003) 32-39
5. Suzuki, J., Isozaki, H., Maeda, E.: Convolution kernels with feature selection for natural language processing tasks. In: ACL. (2004) 119-126
6. Sleator, D.D., Temperley, D.: Parsing english with a link grammar. Technical Report CMU-CS-91-196, Department of Computer Science, Carnegie Mellon University, Pittsburgh, PA (1991)
7. Pyysalo, S., Ginter, F., Pahikkala, T., Boberg, J., Järvinen, J., Salakoski, T., Koivula, J.: Analysis of link gram mar on biomedical dependency corpus targeted at protein-protein interactions. In Collier, N., Ruch, P., Nazarenko, A., eds.: Proceedings of the JNLPBA workshop at COLING'04, Geneva, (2004) 16-21
8. Tsivtsivadze, E., Pahikkala, T., Pyysalo, S., Boberg, J., Mylläri, A., Salakoski, T.: Regularized least-squares for parse ranking. In: Proceedings of the 6th International Symposium on Intelligent Data Analysis, Springer-Verlag (2006) 464-474 Copyright Springer-Verlag Berlin Heidelberg 2006.
9. Poggio, T., Smale, S.: The mathematics of learning: Dealing with data. Amer. Math. Soc. Notice 50 (2003) 637-644
10. Kendall, M.G.: Rank Correlation Methods. 4, edn. Griffin, London (1970)
11. Haussler, D.: Convolution kernels on discrete structures. Technical Report UCSCCRL-99-10, UC Santa Cruz (1999)
12. Schölkopf, B., Herbrich, R., Smola, A.J.: A generalized representer theorem. In Helmbold, D., Williamson, R., eds.: Proceedings of the 14th Annual Conference on Computational Learning Theory and and 6th European Conference on Computational Learning Theory, Berlin, Germany, Springer-Verlag (2001) 416-426
13. Lodhi, H., Saunders, C., Shawe-Taylor, J., Cristianini, N., Watkins, C.J.C.H.: Text classification using string kernels. Journal of Machine Learning Research 2 (2002) 419-444
14. Pahikkala, T., Pyysalo, S., Ginter, F., Boberg, J., Järvinen, J., Salakoski, T.: Kernels incorporating word positional information in natural language disambiguation tasks, In Russell, I., Markov, Z., eds.: Proceedings of the Eighteenth International Florida Artificial Intelligence Research Society Conference, Menlo Park, Ca., AAAI Press (2006) 442-447 Copyright AAAI Press, http://www.aaai.org/.
15. Pahikkala, T., Pyysalo, S., Boberg, J., Mylläri, A., Salakoski, T.: Improving the performance of bayesian and support vector classifiers in word sense disambiguation using positional information. In Honkela, T., Könönen, V., Pöllä, M., Simula, O., eds.: Proceedings of the International and Interdisciplinary Conference on Adaptive Knowledge Representation and Reasoning, Espoo, Finland, Helsinki University of Technology (2005) 90-97
16. Zien, A., Ratsch, G., Mika, S., Scholkopf, B., Lengauer, T., Muller, K.R.: Engineering support vector machine kernels that recognize translation initiation sites. Bioinformatics 16 (2000) 799-807