UT ML Group: Publication: Natural Language Learning

Natural language processing systems are difficult to build, and machine learning methods can help automate their construction significantly. Our research in learning for natural language has mainly involved applying statistical relational learning, inductive logic programming, explanation-based learning, and other learning techniques to automatically construct semantic parsers (e.g. database interfaces) and information extraction systems from training examples. However, we have also conducted research in learning for syntactic parsing, machine translation, language generation, word-sense disambiguation, morphology (past tense generation), and schema-based narrative understanding. Our on-going work is focussed on learning to connect language and perception.

Demos of learning natural-language interfaces:

Publications

Also see


  1. Learning a Compositional Semantic Parser using an Existing Syntactic Parser [Abstract] [PDF] [Slide]
    Ruifang Ge and Raymond J. Mooney
    In the Joint Conference of the 47th Annual Meeting of the Association for Computational Linguistics and the 4th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing (ACL-IJCNLP 2009), pp. 611--619, Suntec, Singapore, August 2009.

  2. A Dependency-based Word Subsequence Kernel [Abstract] [PDF]
    Rohit J. Kate
    In Proceedings of the conference on Empirical Methods in Natural Language Processing (EMNLP-2008) , pp. 400-409, Waikiki, Honolulu, Hawaii, October 2008.

  3. Transforming Meaning Representation Grammars to Improve Semantic Parsing [Abstract] [PDF]
    Rohit J. Kate
    In Proceedings of the Twelfth Conference on Computational Natural Language Learning (CoNLL-2008) , pp. 33-40, Manchester, UK, August 2008.

  4. Learning to Sportscast: A Test of Grounded Language Acquisition [Abstract] [PDF]
    David L. Chen and Raymond J. Mooney
    In Proceedings of the 25th International Conference on Machine Learning (ICML) , Helsinki, Finland, July 2008.

  5. Learning to Connect Language and Perception [Abstract] [PDF]
    Raymond J. Mooney
    In Proceedings of the 23rd AAAI Conference on Artificial Intelligence (AAAI), Senior Member Paper, Chicago, IL, pp. 1598-1601, July 2008.

  6. Learning for Semantic Parsing with Kernels under Various Forms of Supervision [Abstract] [PDF]
    Rohit J. Kate
    Ph.D. Thesis, Department of Computer Sciences, University of Texas at Austin, August 2007.
    159 pages.

  7. Learning for Semantic Parsing and Natural Language Generation Using Statistical Machine Translation Techniques [Abstract] [PDF]
    Yuk Wah Wong
    Ph.D. Thesis, Department of Computer Sciences, University of Texas at Austin, August 2007.
    188 pages.
    Also appears as Technical Report AI07-343, Artificial Intelligence Lab, University of Texas at Austin, August 2007.

  8. Learning for Information Extraction: From Named Entity Recognition and Disambiguation To Relation Extraction [Abstract] [PDF]
    Razvan Constantin Bunescu
    Ph.D. Thesis, Department of Computer Sciences, University of Texas at Austin, August 2007.
    150 pages.
    Also appears as Technical Report AI07-345, Artificial Intelligence Lab, University of Texas at Austin, August 2007.

  9. Learning to Extract Relations from the Web using Minimal Supervision [Abstract] [PDF]
    Razvan C. Bunescu and Raymond J. Mooney
    In Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics (ACL) , Prague, Czech Republic, pp. 576--583, June 2007.

  10. Learning Language Semantics from Ambiguous Supervision [Abstract] [PDF]
    Rohit J. Kate and Raymond J. Mooney
    In Proceedings of the 22nd AAAI Conference on Artificial Intelligence (AAAI-2007), Vancouver, BC, pp. 895-900, July 2007.

  11. Learning Synchronous Grammars for Semantic Parsing with Lambda Calculus [Abstract] [PDF]
    Yuk Wah Wong and Raymond J. Mooney
    Best Paper Award
    In Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics (ACL-2007), pp. 960-967, Prague, Czech Republic, June 2007.

  12. Semi-Supervised Learning for Semantic Parsing using Support Vector Machines [Abstract] [PDF]
    Rohit J. Kate and Raymond J. Mooney
    In Proceedings of the Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, Short Papers (NAACL/HLT-2007), pp. 81-84, Rochester, NY, April 2007.

  13. Generation by Inverting a Semantic Parser That Uses Statistical Machine Translation [Abstract] [PDF]
    Yuk Wah Wong and Raymond J. Mooney
    In Proceedings of the Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics (NAACL/HLT-2007), pp. 172-179, Rochester, NY, April 2007.

  14. Learning for Semantic Parsing [Abstract] [PDF]
    Raymond J. Mooney
    Computational Linguistics and Intelligent Text Processing: Proceedings of the 8th International Conference, CICLing 2007, Mexico City (invited paper), A. Gelbukh (Ed.), pp. 311-324, Springer, Berlin, Germany, February 2007.

  15. Extracting Relations from Text: From Word Sequences to Dependency Paths [Abstract] [PDF]
    Razvan C. Bunescu and Raymond J. Mooney
    Text Mining and Natural Language Processing, Anne Kao and Steve Poteet (eds.), pp. 29-44, Springer, 2007.

  16. Statistical Relational Learning for Natural Language Information Extraction [Abstract] [PDF]
    Razvan Bunescu and Raymond J. Mooney
    Introduction to Statistical Relational Learning, Getoor, L. and Taskar, B. (Eds.), pp. 535-552, MIT Press, Cambridge, MA, 2007.

  17. Learning Language from Perceptual Context: A Challenge Problem for AI [Abstract] [PDF]
    Raymond J. Mooney
    In Proceedings of the 2006 AAAI Fellows Symposium, Boston, MA, July 2006.

  18. Using String-Kernels for Learning Semantic Parsers [Abstract] [PDF]
    Rohit J. Kate and Raymond J. Mooney
    In Proceedings of the Joint 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics (COLING/ACL-2006), pp. 913-920, Sydney, Australia, July 2006.

  19. Discriminative Reranking for Semantic Parsing [Abstract] [PDF]
    Ruifang Ge and Raymond J. Mooney
    In Proceedings of the COLING/ACL-2006 Main Conference Poster Sessions, pp. 263-270, Sydney, Australia, July 2006.

  20. Integrating Co-occurrence Statistics with Information Extraction for Robust Retrieval of Protein Interactions from Medline [Abstract] [PDF]
    Razvan Bunescu, Raymond Mooney, Arun Ramani and Edward Marcotte
    In Proceedings of the HLT-NAACL Workshop on Linking Natural Language Processing and Biology: Towards deeper biological literature analysis (BioNLP-2006), pp. 49-56, New York City, NY, June 2006.

  21. Learning for Semantic Parsing with Statistical Machine Translation [Abstract] [PDF]
    Yuk Wah Wong and Raymond J. Mooney
    In Proceedings of the Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics (HLT/NAACL-2006), pp. 439-446, New York City, NY, June 2006.

  22. Using Encyclopedic Knowledge for Named Entity Disambiguation [Abstract] [PDF]
    Razvan Bunescu and Marius Pasca
    In Proceedings of the 11th Conference of the European Chapter of the Association for Computational Linguistics (EACL-06), pp. 9-16, Trento, Italy, April 2006.

  23. Learning Semantic Parsers Using Statistical Syntactic Parsing Techniques [Abstract] [PDF]
    Ruifang Ge
    Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin, February 2006.
    41 pages.
    Also appears as Technical Report UT-AI-TR-06-327, Artificial Intelligence Lab, University of Texas at Austin, February 2006.

  24. Subsequence Kernels for Relation Extraction [Abstract] [PDF]
    Razvan Bunescu and Raymond J. Mooney
    Advances in Neural Information Processing Systems, Vol. 18: Proceedings of the 2005 Conference (NIPS), Y. Weiss, B. Schoelkopf, J. Platt (Eds.), MIT Press, 2006.

  25. A Kernel-based Approach to Learning Semantic Parsers [Abstract] [PDF]
    Rohit J. Kate
    Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin, November 2005.
    34 pages.
    Also appears as Technical Report UT-AI-05-326, Artificial Intelligence Lab, University of Texas at Austin, November 2005.

  26. Learning for Semantic Parsing Using Statistical Machine Translation Techniques [Abstract] [PDF]
    Yuk Wah Wong
    Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin, October 2005.
    53 pages.
    Also appears as Technical Report UT-AI-05-323, Artificial Intelligence Lab, University of Texas at Austin, October 2005.

  27. A Shortest Path Dependency Kernel for Relation Extraction [Abstract] [PDF]
    Bunescu, R. C., and Mooney, R.J.
    Appears in Proceedings of the Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing, Vancouver, B.C., pp. 724--731, October 2005.

  28. Consolidating the Set of Known Human Protein-Protein Interactions in Preparation for Large-Scale Mapping of the Human Interactome [Abstract] [PDF]
    Ramani, A.K., Bunescu, R.C., Mooney, R.J. and Marcotte, E.M.
    Genome Biology, 6, 5, r40(2005).

  29. A Statistical Semantic Parser that Integrates Syntax and Semantics [Abstract] [PDF]
    Ge, R. and Mooney, R.J.
    Proceedings of the Ninth Conference on Computational Natural Language Learning, Ann Arbor, MI, pp. 9--16, June 2005.

  30. Mining Knowledge from Text Using Information Extraction [Abstract] [PDF]
    Mooney, R. J. and Bunescu, R.
    SIGKDD Explorations (special issue on Text Mining and Natural Language Processing), 7, 1 (2005), pp. 3-10.

  31. Using Biomedical Literature Mining to Consolidate the Set of Known Human Protein-Protein Interactions [Abstract] [PDF]
    Ramani, A., Marcotte E., Bunescu, R., and Mooney, R.J.
    Proceedings of the ACL-ISMB Workshop on Linking Biological Literature, Ontologies and Databases: Mining Biological Semantics, pp. 46--53, Detroit, MI, June 2005.

  32. Learning to Transform Natural to Formal Languages [Abstract] [PDF]
    Kate, R.J., Wong, Y. W., and Mooney, R.J.
    Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI-05), Pittsburgh, PA, pp. 1062--1068, July 2005.

  33. Comparative Experiments on Learning Information Extractors for Proteins and their Interactions [Abstract] [PDF]
    Razvan Bunescu, Ruifang Ge, Rohit J. Kate, Edward M. Marcotte, Raymond J. Mooney, Arun Kumar Ramani, and Yuk Wah Wong
    Artificial Intelligence in Medicine (Special Issue on Summarization and Information Extraction from Medical Documents), 33, 2 (2005), pp. 139-155.

  34. Collective Information Extraction with Relational Markov Networks [Abstract] [PDF]
    Razvan Bunescu and Raymond J. Mooney
    Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL-2004), pp. 439-446, Barcelona, Spain, July 2004.

  35. Using Soft-Matching Mined Rules to Improve Information Extraction [Abstract] [PDF]
    Un Yong Nahm and Raymond J. Mooney
    Proceedings of the AAAI-2004 Workshop on Adaptive Text Extraction and Mining (ATEM-2004), pp. 27-32, San Jose, CA, July 2004.

  36. Relational Markov Networks for Collective Information Extraction [Abstract] [PDF]
    Razvan Bunescu and Raymond J. Mooney
    Proceedings of the ICML-2004 Workshop on Statistical Relational Learning and its Connections to Other Fields (SRL-2004), Banff, Canada, July 2004.

  37. Learning Transformation Rules for Semantic Parsing [Abstract] [PDF]
    Rohit J. Kate, Yuk Wah Wong, Ruifang Ge, and Raymond J. Mooney
    Unpublished Technical Note, April 2004.

  38. Learning Semantic Parsers: An Important But Under-Studied Problem [Abstract] [PDF]
    Raymond J. Mooney
    Papers from the AAAI 2004 Spring Symposium on Language Learning: An Interdisciplinary Perspective, pp. 39-44, Stanford, CA, March 2004.

  39. Integrating Top-down and Bottom-up Approaches in Inductive Logic Programming: Applications in Natural Language Processing and Relational Data Mining [Abstract] [PDF]
    Lappoon R. Tang
    Ph.D. Thesis, Department of Computer Sciences, University of Texas at Austin, August 2003.
    219 pages

  40. Learning to Extract Proteins and their Interactions from Medline Abstracts [Abstract] [PDF]
    Razvan Bunescu, Ruifang Ge, Rohit J. Kate, Raymond J. Mooney, Yuk Wah Wong, Edward M. Marcotte, and Arun Kumar Ramani
    Proceedings of the ICML-2003 Workshop on Machine Learning in Bioinformatics, pp.46-53, Washington DC, August 2003.

  41. Bottom-Up Relational Learning of Pattern Matching Rules for Information Extraction [Abstract] [PDF]
    Mary Elaine Califf and Raymond J. Mooney
    Journal of Machine Learning Research, 4, (2003), pp. 177-210.

  42. Acquiring Word-Meaning Mappings for Natural Language Interfaces [Abstract] [PDF]
    Cynthia A. Thompson and Raymond J. Mooney
    Journal of Artificial Intelligence Research, 18, (2003) pp. 1-44.

  43. Associative Anaphora Resolution: A Web-Based Approach [Abstract] [PDF]
    Razvan Bunescu
    Proceedings of the EACL 2003 Workshop on the Computational Treatment of Anaphora, pp. 47-52, Budapest, Hungary, April 2003.

  44. Machine Learning [Abstract] [PDF]
    Raymond J. Mooney
    Oxford Handbook of Computational Linguistics, R. Mitkov (Ed.), Oxford University Press, pp. 376-394, 2003.

  45. Using Multiple Clause Constructors in Inductive Logic Programming for Semantic Parsing [Abstract] [PDF]
    Lappoon R. Tang and Raymond J. Mooney
    Proceedings of the 12th European Conference on Machine Learning (ECML-2001), pp. 466-477, Freiburg, Germany, September 2001.

  46. Automated Construction of Database Interfaces: Integrating Statistical and Relational Learning for Semantic Parsing [Abstract] [PDF]
    Lappoon R. Tang and Raymond J. Mooney
    Proceedings of the Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora (EMNLP/VLC-2000), pp. 133 - 141, Hong Kong, October 2000

  47. A Mutually Beneficial Integration of Data Mining and Information Extraction [Abstract] [PDF]
    Un Yong Nahm and Raymond J. Mooney
    Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI-2000), Austin, TX, pp. 627-632, July 2000.

  48. Integrating Statistical and Relational Learning for Semantic Parsing: Applications to Learning Natural Language Interfaces for Databases [Abstract] [PDF]
    Lappoon R. Tang
    Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin, May 2000.
    50 pages

  49. Learning for Semantic Interpretation: Scaling Up Without Dumbing Down [Abstract] [PDF]
    Raymond J. Mooney
    Workshop Notes for the Workshop on Learning Language in Logic Bled, Slovenia, pp. 7-14, June 1999.
    Also appears in Learning Language in Logic, J. Cussens and S. Dzeroski (Eds.), pp. 57-66, Springer Verlag, Berlin, 2000.

  50. Automatic Construction of Semantic Lexicons for Learning Natural Language Interfaces [Abstract] [PDF]
    Cynthia A. Thompson and Raymond J. Mooney
    Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI-99), Orlando, FL, pp. 487-493, July 1999.

  51. Relational Learning of Pattern-Match Rules for Information Extraction [Abstract] [PDF]
    Mary Elaine Califf and Raymond J. Mooney
    Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI-99), Orlando, FL, pp. 328-334, July 1999.

  52. Active Learning for Natural Language Parsing and Information Extraction [Abstract] [PDF]
    Cynthia A. Thompson, Mary Elaine Califf and Raymond J. Mooney
    Nominated for Best Paper Award
    Proceedings of the Sixteenth International Machine Learning Conference (ICML-99) , Bled, Slovenia, pp. 406-414, June 1999.

  53. Semantic Lexicon Acquisition for Learning Natural Language Interfaces [Abstract] [PDF]
    Cynthia Ann Thompson
    Ph.D. Thesis, Department of Computer Sciences, University of Texas at Austin, December 1998.
    101 pages.
    Also appears as Technical Report AI 99-278, Artificial Intelligence Lab, University of Texas at Austin.

  54. Semantic Lexicon Acquisition for Learning Natural Language Interfaces [Abstract] [PDF]
    Cynthia A. Thompson and Raymond J. Mooney
    Proceedings of the Sixth Workshop on Very Large Corpora, pp. 57-65, Montreal, Quebec, Canada, August 1998.
    TR AI 98-273, Artificial Intelligence Lab, University of Texas at Austin, May 1998.

  55. Relational Learning Techniques for Natural Language Information Extraction [Abstract] [PDF]
    Mary Elaine Califf
    Ph.D. Thesis, Department of Computer Sciences, University of Texas at Austin, August 1998.
    142 pages.
    Also appears as Technical Report AI 98-276, Artificial Intelligence Lab, University of Texas at Austin.

  56. Relational Learning of Pattern-Match Rules for Information Extraction [Abstract] [PDF]
    Mary Elaine Califf and Raymond J. Mooney
    Proceedings of AAAI Spring Symposium on Applying Machine Learning to Discourse Processing, pp. 6-11, Standford, CA, March 1998.

  57. Relational Learning Techniques for Natural Language Information Extraction [Abstract] [PDF]
    Mary Elaine Califf
    Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin, 1997.
    27 pages

  58. Applying ILP-based Techniques to Natural Language Information Extraction: An Experiment in Relational Learning [Abstract] [PDF]
    Mary Elaine Califf and Raymond J. Mooney
    Workshop Notes of the IJCAI-97 Workshop on Frontiers of Inductive Logic Programming, pp. 7-11, Nagoya, Japan, August 1997.

  59. Learning to Parse Natural Language Database Queries into Logical Form [Abstract] [PDF]
    Cynthia A. Thompson Raymond J. Mooney, and Lappoon R. Tang
    Proceedings of the ML-97 Workshop on Automata Induction, Grammatical Inference, and Language Acquisition, Nashville, TN, July 1997.

  60. Relational Learning of Pattern-Match Rules for Information Extraction [Abstract] [PDF]
    Mary Elaine Califf and Raymond J. Mooney
    Proceedings of the ACL Workshop on Natural Language Learning, pp. 9-15, Madrid, Spain, July 1997.

  61. Learning Parse and Translation Decisions From Examples With Rich Context [Abstract] [PDF]
    Ulf Hermjakob and Raymond J. Mooney
    Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics (ACL'97/EACL'97), pp. 482-489, July 1997.

  62. Learning Parse and Translation Decisions From Examples With Rich Context [Abstract] [PDF]
    Ulf Hermjakob
    Ph.D. Thesis, Department of Computer Sciences, University of Texas at Austin, May 1997.
    175 pages.
    Also appears as Technical Report AI 97-12, Artifical Intelligence Lab, University of Texas at Austin.

  63. An Inductive Logic Programming Method for Corpus-based Parser Construction [Abstract] [PDF]
    John M. Zelle and Raymond J. Mooney
    Unpublished Technical Note, January 1997

  64. Semantic Lexicon Acquisition for Learning Parsers [Abstract] [PDF]
    Cynthia A. Thompson and Raymond J. Mooney
    Unpublished Technical Note, January 1997

  65. Inductive Logic Programming for Natural Language Processing [Abstract] [PDF]
    Raymond J. Mooney
    Inductive Logic Programming: Selected Papers from the 6th International Workshop, S. Muggleton (Ed.), pp.3-22, Springer Verlag, Berlin, 1997.
    Also appears in Proceedings of the 6th International Inductive Logic Programming Workshop, pp. 205-224, Stockholm, Sweden, August 1996.

  66. Learning to Parse Database Queries using Inductive Logic Programming [Abstract] [PDF]
    John M. Zelle and Raymond J. Mooney
    Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), pp. 1050-1055, Portland, OR, August 1996.

  67. Comparative Experiments on Disambiguating Word Senses: An Illustration of the Role of Bias in Machine Learning [Abstract] [PDF]
    Raymond J. Mooney
    Proceedings of the 1996 Conference on Empirical Methods in Natural Language Processing (EMNLP-96), pp. 82-91, Philadelphia, PA, May 1996.

  68. Corpus-Based Lexical Acquisition For Semantic Parsing [Abstract] [PDF]
    Cynthia Thompson
    Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin, February 1996.
    38 pages

  69. Lexical Acquisition: A Novel Machine Learning Problem [Abstract] [PDF]
    Cynthia A. Thompson and Raymond J. Mooney
    Technical Report, Artificial Intelligence Lab, University of Texas at Austin, January 1996.

  70. Comparative Results on Using Inductive Logic Programming for Corpus-based Parser Construction [Abstract] [PDF]
    John M. Zelle and Raymond J. Mooney
    Symbolic, Connectionist, and Statistical Approaches to Learning for Natural Language Processing, S. Wermter, E. Riloff and G. Scheler (Eds.), Spring Verlag, 1996.

  71. Learning the Past Tense of English Verbs Using Inductive Logic Programming [Abstract] [PDF]
    Raymond J. Mooney and Mary Elaine Califf
    Symbolic, Connectionist, and Statistical Approaches to Learning for Natural Language Processing, S. Wermter, E. Riloff and G. Scheler (Eds.), Spring Verlag, 1996.

  72. Inducing Logic Programs without Explicit Negative Examples [Abstract] [PDF]
    John M. Zelle, Cynthia A. Thompson, Mary Elaine Califf, and Raymond J. Mooney
    Proceedings of the Fifth International Workshop on Inductive Logic Programming, pp. 403-416, Leuven, Belguim, Sepetember 1995.

  73. Using Inductive Logic Programming to Automate the Construction of Natural Language Parsers [Abstract] [PDF]
    John M. Zelle
    Ph.D. Thesis, Department of Computer Sciences, University of Texas at Austin, August 1995.
    204 pages
    Also appears as Technical Report AI 96-249, Department of Computer Sciences, University of Texas at Austin

  74. A Comparison of Two Methods Employing Inductive Logic Programming for Corpus-based Parser Constuction [Abstract] [PDF]
    John M. Zelle and Raymond J. Mooney
    Working Notes of the IJCAI-95 Workshop on New Approaches to Learning for Natural Language Processing, pp.79-86, Montreal, Quebec, Canada, August 1995.

  75. Acquisition of a Lexicon from Semantic Representations of Sentences [Abstract] [PDF]
    Cynthia A. Thompson
    Proceedings of the 33rd Annual Meeting of the Association of Computational Linguistics (ACL-95), pp. 335-337, Boston, MA, July 1995.

  76. Induction of First-Order Decision Lists: Results on Learning the Past Tense of English Verbs [Abstract] [PDF]
    Raymond J. Mooney and Mary Elaine Califf
    Journal of Artificial Intelligence Research, 3 (1995) pp. 1-24.

  77. Inducing Deterministic Prolog Parsers From Treebanks: A Machine Learning Approach [Abstract] [PDF]
    John M. Zelle and Raymond J. Mooney
    Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), pp. 748-753, Seattle, WA, July 1994.

  78. Learning Semantic Grammars With Constructive Inductive Logic Programming [Abstract] [PDF]
    John M. Zelle and Raymond J. Mooney
    Proceedings of the Eleventh National Conference of the American Association for Artificial Intelligence (AAAI-93), pp. 817-822, Washington, D.C. July 1993.

  79. Learning Search-Control Heuristics for Logic Programs: Applications to Speedup Learning and Language Acquisition [Abstract] [PDF]
    John M. Zelle
    Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin, March 1993.
    36 pages

  80. Learning Plan Schemata From Observation: Explanation-Based Learning for Plan Recognition [Abstract] [PDF]
    Raymond J. Mooney
    Cognitive Science, 14, 4 (1990), pp. 483--509.

  81. Integrated Learning of Words and their Underlying Concepts [Abstract] [PDF]
    Raymond J. Mooney
    In Proceedings of the Ninth Annual Conference of the Cognitive Science Society (CogSci), pp. 974-978, Seattle, WA, July 1987.

  82. Learning Schemata for Natural Language Processing [Abstract] [PDF]
    Raymond J. Mooney and Gerald F. DeJong
    In Proceedings of the Ninth International Joint Conference on Artificial Intelligence (IJCAI), pp. 681-687, Los Angeles, CA, August 1985.

mooney@cs.utexas.edu