Learning context-free grammar using improved tabular representation

Applied Soft Computing Journal

Volumn 10, Issue 1, 2010, Pages 44-52

  Unold, Olgierd ^a   Jaworski, Marcin ^a  

^a WROCLAW UNIVERSITY OF TECHNOLOGY   (Poland)

Author keywords

Context free grammar; CYK algorithm; Genetic algorithm; Grammatical inference; Partitioning problem

Indexed keywords

2-GROUP; BLOCK SIZES; CHOMSKY NORMAL FORM; CYK ALGORITHM; FITNESS FUNCTIONS; GRAMMAR INDUCTION; GRAMMAR LEARNING; GRAMMATICAL INFERENCE; GRAMMATICAL STRUCTURE; HARDNESS OF LEARNING; INITIAL POPULATION; LEARNING CONTEXT; MACHINE-LEARNING; NP-HARD; PARTIAL KNOWLEDGE; PARTITIONING PROBLEM; POPULATION SIZES; STRUCTURAL INFORMATION;

COMMUNICATION CHANNELS (INFORMATION THEORY); COMPUTATIONAL COMPLEXITY; COMPUTATIONAL GRAMMARS; COMPUTATIONAL LINGUISTICS; COMPUTER SIMULATION; EDUCATION; FORMAL LANGUAGES; FUNCTION EVALUATION; GENETIC ALGORITHMS; INFERENCE ENGINES; MATHEMATICAL OPERATORS; PATTERN RECOGNITION; POPULATION STATISTICS; SET THEORY;

LEARNING ALGORITHMS;

EID: 70350113841     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2009.06.006     Document Type: Article

References (48)

1. Abe N., and Mamitsuka H. Predicting protein secondary structure using Stochastic tree grammars. Machine Learning Journal 29 (1997) 275-301
2. P. Adriaans, Language Learning from a Categorical Perspective, Ph.D. thesis, Universiteit van Amsterdam, 1992.
3. In: Adriaans P., Fernau H., van M., and Zaannen (Eds). Grammatical Inference: Algorithms and Applications, Proceedings of ICGI 00, LNAI 2484 (2002), Springer-Verlag, Berlin, Heidelberg
4. Arimura H., Sakamoto H., and Arikawa S. Ecient Learning of Semistructured Data from Queries. In: Abe N., Khardon R., and Zeugmann T. (Eds). Proceedings of ALT 2001, LNCS 2225 (2001)
5. Baker J.K. Trainable Grammars for Speech Recognition. In: Klatt D.H., and Wolf J.J. (Eds). Speech Communication Papers for the 97th Meeting of the Acoustical Society of America (1979)
6. Carrasco R.C., Oncina J., and Calera-Rubio J. Stochastic inference of regular tree languages. Machine Learning Journal 44 1 (2001) 185-197
7. Charniak E. Statistical Language Learning (1993), MIT Press, Cambridge
8. Chidlovskii B. Schema Extraction from XML: A Grammatical Inference Approach. In: Lenzerini M., Nardi D., Nutt W., and Suciu D. (Eds). Proceedings of the 8th International Workshop on Knowledge Representation meets Databases (KRDB 2001), Vol. 45 of CEUR Workshop Proceedings (2001)
9. J. Cocke, Programming Languages and Their Compilers: Preliminary Notes, Tech. Rep., Courant Institute of Mathematical Sciences, New York University, 1966.
10. Crepinsek M., Mernik M., Javed F., Bryant B., and Sprague A. Extracting grammar from programs: evolutionary approach. ACM Sigplan 40 (2005) 39-46
11. de la Higuera C. Current Trends in Grammatical Inference. In: Ferri F., Inesta J., Admin A., and Pudil P. (Eds). Advances in Pattern Recognition. Joint IAPR International Workshops SSPR+SPR'2000, LNCS 1876 (2000), Springer Verlag, Berlin
12. de la Higuera C., and Oncina J. Learning Deterministic Linear Languages. In: Kivinen J., and Sloan R.H. (Eds). Proceedings of COLT 2002, LNAI 2375 (2002), Springer-Verlag, Berlin, Heidelberg
13. Dupont P. Regular Grammatical Inference from Positive and Negative Samples by Genetic Search: the GIG Method (1994), Springer-Verlag
14. H. Fernau, Learning XML grammars, in: P. Perner et al. (Eds.), Machine Learning and Data Mining in Pattern Recognition MLDM01, Springer-Verlag, 2001.
15. P. García, J. Oncina, Inference of recognizable tree sets, Tech. Re DSIC-II/47/93, Departamento de Lenguajes y Sistemas Informaticos, Universidad Politecnica de Valencia, 1993.
16. Gold E. Language identification in the limit. Information and Control 10 5 (1967) 447-474
17. A. Habrard, M. Bernard, F. Jacquenet, Generalized Stochastic Tree Automata for Multi-relational Data Mining, in: Adriaans et al. [3], pp. 125-133.
18. Jagota A., Lyngso R.B., and Pedersen C.N.S. Comparing a Hidden Markov Model and a Stochastic Context-Free Grammar. Proceedings of WABI 01 (2001), Springer-Verlag, Berlin, Heidelberg
19. T. Kasami, An Efficient Recognition and Syntax-analysis Algorithm for Context-free Languages, Tech. Re AFCRL-65-558, Air Force Cambridge Research Laboratory, Bedford, Massachusetts, 1965.
20. Knuutila T., and Steinby M. Inference of tree languages from a finite sample: an algebraic approach. Theoretical Computer Science 129 (1994) 337-367
21. Koshiba T., Mákinen E., and Takada Y. Inferring pure context-free languages from positive data. Acta Cybernetica 14 3 (2000) 469-477
22. Kremer S.C. Parallel Stochastic Grammar Induction. Proceedings of the 1997 International Conference on Neural Networks (ICNN 97), vol. I (1997)
23. L. Lee, Learning of context-free languages: A Survey of the Literature, Tech. Re TR-12-96, Harvard University, Cambridge, Massachusetts, 1996.
24. Lucas S. Structuring Chromosomes for Context-Free Grammar Evolution. 1st International Conference on Evolutionary Computing (1994)
25. Makinan E. A note on the grammatical inference problem for even linear languages. Fundamenta Informaticae 25 2 (1996) 175-182
26. Michalewicz Z. Genetic Algorithms + Data Structures = Evolution Programs (1996), Springer, Berlin
27. Nakamura K. Incremental Learning of Context Free Grammars by Extended Inductive CYK Algorithm. In: de la Higuera C., Adriaans P., van Zaanen M., and Oncina J. (Eds). Proceedings of the Workshop and Tutorial on Learning Contex-Free Grammars, ECML 2003 (2003), Ruder Boskovic Institute, Cavtat-Dubrovnik, Croatia
28. Nevill-Manning C., and Witten I. Identifying hierarchical structure in sequences: a linear-time algorithm. Journal of Artificial Intelligence Research 7 (1997) 67-82
29. J.R. Rico-Juan, J. Calera-Rubio, R.C. Carrasco, Stochastic k-testable Tree Languages and Applications, in: Adriaans et al. [3], pp. 199-212.
30. Sakakibara Y. Learning Context-free grammars from structural data in polynomial time. Theoretical Computer Science 76 (1990) 223-242
31. Sakakibara Y. Efficient learning of context-free grammars from positive structural examples. Information and Computation 97 (1992) 23-60
32. Sakakibara Y. Learning context-free grammars using tabular representations. Pattern Recognition 38 (2005) 1372-1383
33. Sakakibara Y., Brown M., Hughley R., Mian I., Sjolander K., Underwood R., and Haussler D. Stochastic context-free grammars for tRNA modeling. Nuclear Acids Research 22 (1994) 5112-5120
34. Sakakibara Y., and Kondo M. GA-based learning of context-free grammars using tabular representations. Proceedings of 16th International Conference in Machine Learning (ICML-99) (1999), Morgan-Kaufmann, Los Altos, CA
35. Sakakibara Y., and Muramatsu H. Context-free grammars from partially structured examples. Proceedings of 15th International Colloquium on Grammatical Inference (ICGI-2000)), LNAI 1891 (2000), Springer, Berlin
36. Salvador I., and Benedí J.M. Rna modeling by combining stochastic context-free grammars and n-gram models. International Journal of Pattern Recognition and Artificial Intelligence 16 3 (2002) 309-316
37. Sempere J.M., and García P. A Characterisation of Even Linear Languages and its Application to the Learning Problem (1994), Springer-Verlag
38. Stolcke A. An Efficient probablistic context-free parsing algorithm that computes prefix probabilities. Comp. Linguistics 21 2 (1995) 165-201
39. Takada Y. Grammatical inference for even linear languages based on control sets. Information Processing Letters 28 (1988) 193-199
40. Takada Y. A Hierarchy of Language Families Learnable by Regular Language Learners (1994), Springer-Verlag
41. Tanaka E. Theoretical aspects of syntactic pattern recognition. Pattern Recognition 28 7 (1995) 1053-1061
42. O. Unold, Context-free grammar induction with grammar-based classifier system, Archives of Control Science 15 (LI) (4) (2005) 681-690.
43. O. Unold, Grammar-based classifier system for recognition of promoter regions, in: B. Beliczynski et al. (Eds.), Proceedings of ICANNGA07, LNCS 4431, Part I, 2007.
44. O. Unold, Learning classifier system approach to natural language grammar induction, in: Y. Shi et al. (Eds.), Proceedings of ICCS 2007. LNCS 4488, Part II, 2007.
45. Unold O., and Cielecki L. Learning context-free grammars from partially structured examples: Juxtaposition of GCS with TBL. 7th International Conference on Hybrid Intelligent Systems (2007), IEEE Computer Society Press, Germany
46. von Laszewski G. Intelligent structural operators for the k-way graph partitioning problem. Proceedings of Fourth International Conference on Genetic Algorithms (1991), Morgan Kaufmann, Los Altos, CA
47. Wyard P. Representational Issues for Context Free Grammar Induction Using Genetic Algorithms (1994), Springer-Verlag
48. 3. Information and Control 10 2 (1967) 189-208