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Raymond J. Mooney: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Gerald DeJong, Raymond J. Mooney
    Explanation-Based Learning: An Alternative View. [Citation Graph (4, 0)][DBLP]
    Machine Learning, 1986, v:1, n:2, pp:145-176 [Journal]
  2. Dirk Ourston, Raymond J. Mooney
    Changing the Rules: A Comprehensive Approach to Theory Refinement. [Citation Graph (1, 0)][DBLP]
    AAAI, 1990, pp:815-820 [Conf]
  3. Bradley L. Richards, Raymond J. Mooney
    First-Order Theory Revision. [Citation Graph (1, 0)][DBLP]
    ML, 1991, pp:447-451 [Conf]
  4. Raymond J. Mooney, Mary Elaine Califf
    Induction of First-Order Decision Lists: Results on Learning the Past Tense of English Verbs. [Citation Graph (1, 0)][DBLP]
    J. Artif. Intell. Res. (JAIR), 1995, v:3, n:, pp:1-24 [Journal]
  5. Jude W. Shavlik, Raymond J. Mooney, Geoffrey G. Towell
    Symbolic and Neural Learning Algorithms: An Experimental Comparison. [Citation Graph (1, 0)][DBLP]
    Machine Learning, 1991, v:6, n:, pp:111-143 [Journal]
  6. Paul T. Baffes, Raymond J. Mooney
    A Novel Application of Theory Refinement to Student Modeling. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, Vol. 1, 1996, pp:403-408 [Conf]
  7. Mary Elaine Califf, Raymond J. Mooney
    Relational Learning of Pattern-Match Rules for Information Extraction. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 1999, pp:328-334 [Conf]
  8. Tara A. Estlin, Raymond J. Mooney
    Multi-Strategy Learning of Search Control for Partial-Order Planning. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, Vol. 1, 1996, pp:843-848 [Conf]
  9. Rohit J. Kate, Yuk Wah Wong, Raymond J. Mooney
    Learning to Transform Natural to Formal Languages. [Citation Graph (0, 0)][DBLP]
    AAAI, 2005, pp:1062-1068 [Conf]
  10. Hwee Tou Ng, Raymond J. Mooney
    On the Role of Coherence in Abductive Explanation. [Citation Graph (0, 0)][DBLP]
    AAAI, 1990, pp:337-342 [Conf]
  11. Hwee Tou Ng, Raymond J. Mooney
    An Efficient First-Order Horn-Clause Abduction System Based on the ATMS. [Citation Graph (0, 0)][DBLP]
    AAAI, 1991, pp:494-499 [Conf]
  12. Prem Melville, Raymond J. Mooney, Ramadass Nagarajan
    Content-Boosted Collaborative Filtering for Improved Recommendations. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 2002, pp:187-192 [Conf]
  13. Raymond J. Mooney, Scott Bennett
    A Domain Independent Explanation-Based Generalizer. [Citation Graph (0, 0)][DBLP]
    AAAI, 1986, pp:551-555 [Conf]
  14. Un Yong Nahm, Raymond J. Mooney
    A Mutually Beneficial Integration of Data Mining and Information Extraction. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 2000, pp:627-632 [Conf]
  15. Bradley L. Richards, Raymond J. Mooney
    Learning Relations by Pathfinding. [Citation Graph (0, 0)][DBLP]
    AAAI, 1992, pp:50-55 [Conf]
  16. Siddarth Subramanian, Raymond J. Mooney
    Qualitative Multiple-Fault Diagnosis of Continuous Dynamic Systems Using Behavioral Modes. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, Vol. 2, 1996, pp:965-970 [Conf]
  17. Cynthia A. Thompson, Raymond J. Mooney
    Inductive Learning For Abductive Diagnosis. [Citation Graph (0, 0)][DBLP]
    AAAI, 1994, pp:664-669 [Conf]
  18. Cynthia A. Thompson, Raymond J. Mooney
    Automatic Construction of Semantic Lexicons for Learning Natural Language Interfaces. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 1999, pp:487-493 [Conf]
  19. John M. Zelle, Raymond J. Mooney
    Learning Semantic Grammars with Constructive Inductive Logic Programming. [Citation Graph (0, 0)][DBLP]
    AAAI, 1993, pp:817-822 [Conf]
  20. John M. Zelle, Raymond J. Mooney
    Inducing Deterministic Prolog Parsers from Treebanks: A Machine Learning Approach. [Citation Graph (0, 0)][DBLP]
    AAAI, 1994, pp:748-753 [Conf]
  21. John M. Zelle, Raymond J. Mooney
    Learning to Parse Database Queries Using Inductive Logic Programming. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, Vol. 2, 1996, pp:1050-1055 [Conf]
  22. Razvan C. Bunescu, Raymond J. Mooney
    Collective Information Extraction with Relational Markov Networks. [Citation Graph (0, 0)][DBLP]
    ACL, 2004, pp:438-445 [Conf]
  23. Ruifang Ge, Raymond J. Mooney
    Discriminative Reranking for Semantic Parsing. [Citation Graph (0, 0)][DBLP]
    ACL, 2006, pp:- [Conf]
  24. Ulf Hermjakob, Raymond J. Mooney
    Learning Parse and Translation Decisions from Examples with Rich Context. [Citation Graph (0, 0)][DBLP]
    ACL, 1997, pp:482-489 [Conf]
  25. Rohit J. Kate, Raymond J. Mooney
    Using String-Kernels for Learning Semantic Parsers. [Citation Graph (0, 0)][DBLP]
    ACL, 2006, pp:- [Conf]
  26. Raymond J. Mooney
    Learning for Semantic Parsing. [Citation Graph (0, 0)][DBLP]
    CICLing, 2007, pp:311-324 [Conf]
  27. Un Yong Nahm, Raymond J. Mooney
    Mining soft-matching association rules. [Citation Graph (0, 0)][DBLP]
    CIKM, 2002, pp:681-683 [Conf]
  28. Raymond J. Mooney, Loriene Roy
    Content-based book recommending using learning for text categorization. [Citation Graph (0, 0)][DBLP]
    ACM DL, 2000, pp:195-204 [Conf]
  29. Prem Melville, Stewart M. Yang, Maytal Saar-Tsechansky, Raymond J. Mooney
    Active Learning for Probability Estimation Using Jensen-Shannon Divergence. [Citation Graph (0, 0)][DBLP]
    ECML, 2005, pp:268-279 [Conf]
  30. Yuk Lai Suen, Prem Melville, Raymond J. Mooney
    Combining Bias and Variance Reduction Techniques for Regression Trees. [Citation Graph (0, 0)][DBLP]
    ECML, 2005, pp:741-749 [Conf]
  31. Lappoon R. Tang, Raymond J. Mooney
    Using Multiple Clause Constructors in Inductive Logic Programming for Semantic Parsing. [Citation Graph (0, 0)][DBLP]
    ECML, 2001, pp:466-477 [Conf]
  32. Lilyana Mihalkova, Raymond J. Mooney
    Using Active Relocation to Aid Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 2006, pp:580-585 [Conf]
  33. Jonathan Wildstrom, Peter Stone, Emmett Witchel, Raymond J. Mooney, Michael Dahlin
    Towards Self-Configuring Hardware for Distributed Computer Systems. [Citation Graph (0, 0)][DBLP]
    ICAC, 2005, pp:241-249 [Conf]
  34. Prem Melville, Foster J. Provost, Raymond J. Mooney
    An Expected Utility Approach to Active Feature-Value Acquisition. [Citation Graph (0, 0)][DBLP]
    ICDM, 2005, pp:745-748 [Conf]
  35. Prem Melville, Maytal Saar-Tsechansky, Foster J. Provost, Raymond J. Mooney
    Active Feature-Value Acquisition for Classifier Induction. [Citation Graph (0, 0)][DBLP]
    ICDM, 2004, pp:483-486 [Conf]
  36. Mikhail Bilenko, Beena Kamath, Raymond J. Mooney
    Adaptive Blocking: Learning to Scale Up Record Linkage. [Citation Graph (0, 0)][DBLP]
    ICDM, 2006, pp:87-96 [Conf]
  37. Sugato Basu, Arindam Banerjee, Raymond J. Mooney
    Semi-supervised Clustering by Seeding. [Citation Graph (0, 0)][DBLP]
    ICML, 2002, pp:27-34 [Conf]
  38. Mikhail Bilenko, Sugato Basu, Raymond J. Mooney
    Integrating constraints and metric learning in semi-supervised clustering. [Citation Graph (0, 0)][DBLP]
    ICML, 2004, pp:- [Conf]
  39. Douglas H. Fisher, Kathleen B. McKusick, Raymond J. Mooney, Jude W. Shavlik, Geoffrey G. Towell
    Processing Issues in Comparisons of Symbolic and Connectionist Learning Systems. [Citation Graph (0, 0)][DBLP]
    ML, 1989, pp:169-173 [Conf]
  40. Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Raymond J. Mooney
    Semi-supervised graph clustering: a kernel approach. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:457-464 [Conf]
  41. Prem Melville, Raymond J. Mooney
    Diverse ensembles for active learning. [Citation Graph (0, 0)][DBLP]
    ICML, 2004, pp:- [Conf]
  42. J. Jeffrey Mahoney, Raymond J. Mooney
    Comparing Methods for Refining Certainty-Factor Rule-Bases. [Citation Graph (0, 0)][DBLP]
    ICML, 1994, pp:173-180 [Conf]
  43. Raymond J. Mooney
    Generalizing the Order of Operators in Macro-Operators. [Citation Graph (0, 0)][DBLP]
    ML, 1988, pp:270-283 [Conf]
  44. Raymond J. Mooney, Dirk Ourston
    Induction Over the Unexplained: Integrated Learning of Concepts with Both Explainable and Conventional Aspects. [Citation Graph (0, 0)][DBLP]
    ML, 1989, pp:5-7 [Conf]
  45. Raymond J. Mooney, Dirk Ourston
    Constructive Induction in Theory Refinement. [Citation Graph (0, 0)][DBLP]
    ML, 1991, pp:178-182 [Conf]
  46. Dirk Ourston, Raymond J. Mooney
    Improving Shared Rules in Multiple Category Domain Theories. [Citation Graph (0, 0)][DBLP]
    ML, 1991, pp:534-538 [Conf]
  47. Sowmya Ramachandran, Raymond J. Mooney
    Theory Refinement of Bayesian Networks with Hidden Variables. [Citation Graph (0, 0)][DBLP]
    ICML, 1998, pp:454-462 [Conf]
  48. Cynthia A. Thompson, Mary Elaine Califf, Raymond J. Mooney
    Active Learning for Natural Language Parsing and Information Extraction. [Citation Graph (0, 0)][DBLP]
    ICML, 1999, pp:406-414 [Conf]
  49. John M. Zelle, Raymond J. Mooney, Joshua B. Konvisser
    Combining Top-down and Bottom-up Techniques in Inductive Logic Programming. [Citation Graph (0, 0)][DBLP]
    ICML, 1994, pp:343-351 [Conf]
  50. Paul T. Baffes, Raymond J. Mooney
    Symbolic Revision of Theories with M-of-N Rules. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1993, pp:1135-1142 [Conf]
  51. Mikhail Bilenko, Raymond J. Mooney
    Employing Trainable String Similarity Metrics for Information Integration. [Citation Graph (0, 0)][DBLP]
    IIWeb, 2003, pp:67-72 [Conf]
  52. Tara A. Estlin, Raymond J. Mooney
    Learning to Improve both Efficiency and Quality of Planning. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1997, pp:1227-1233 [Conf]
  53. Prem Melville, Raymond J. Mooney
    Constructing Diverse Classifier Ensembles using Artificial Training Examples. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2003, pp:505-512 [Conf]
  54. Raymond J. Mooney
    The Effect of Rule Use on the Utility of Explanation-Based Learning. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1989, pp:725-730 [Conf]
  55. Raymond J. Mooney, Mary Elaine Califf
    Learning the past tense of English verbs using inductive logic programming. [Citation Graph (0, 0)][DBLP]
    Learning for Natural Language Processing, 1995, pp:370-384 [Conf]
  56. Raymond J. Mooney, Gerald DeJong
    Learning Schemata for Natural Language Processing. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1985, pp:681-687 [Conf]
  57. Raymond J. Mooney, Jude W. Shavlik, Geoffrey G. Towell, Alan Gove
    An Experimental Comparison of Symbolic and Connectionist Learning Algorithms. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1989, pp:775-780 [Conf]
  58. Un Yong Nahm, Raymond J. Mooney
    Mining Soft-Matching Rules from Textual Data. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2001, pp:979-986 [Conf]
  59. John M. Zelle, Raymond J. Mooney
    Combining FOIL and EBG to Speed-up Logic Programs. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1993, pp:1106-1113 [Conf]
  60. John M. Zelle, Raymond J. Mooney
    Comparative results on using inductive logic programming for corpus-based parser construction. [Citation Graph (0, 0)][DBLP]
    Learning for Natural Language Processing, 1995, pp:355-369 [Conf]
  61. Raymond J. Mooney
    Inductive Logic Programming for Natural Language Processing. [Citation Graph (0, 0)][DBLP]
    Inductive Logic Programming Workshop, 1996, pp:3-22 [Conf]
  62. Mikhail Bilenko, Raymond J. Mooney
    Adaptive duplicate detection using learnable string similarity measures. [Citation Graph (0, 0)][DBLP]
    KDD, 2003, pp:39-48 [Conf]
  63. Arindam Banerjee, Chase Krumpelman, Joydeep Ghosh, Sugato Basu, Raymond J. Mooney
    Model-based overlapping clustering. [Citation Graph (0, 0)][DBLP]
    KDD, 2005, pp:532-537 [Conf]
  64. Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
    A probabilistic framework for semi-supervised clustering. [Citation Graph (0, 0)][DBLP]
    KDD, 2004, pp:59-68 [Conf]
  65. Sugato Basu, Raymond J. Mooney, Krupakar V. Pasupuleti, Joydeep Ghosh
    Evaluating the novelty of text-mined rules using lexical knowledge. [Citation Graph (0, 0)][DBLP]
    KDD, 2001, pp:233-238 [Conf]
  66. Hwee Tou Ng, Raymond J. Mooney
    Abductive Plan Recognition and Diagnosis: A Comprehensive Empirical Evaluation. [Citation Graph (0, 0)][DBLP]
    KR, 1992, pp:499-508 [Conf]
  67. Raymond J. Mooney
    Learning for Semantic Interpretation: Scaling Up without Dumbing Down. [Citation Graph (0, 0)][DBLP]
    Learning Language in Logic, 1999, pp:57-66 [Conf]
  68. Prem Melville, Nishit Shah, Lilyana Mihalkova, Raymond J. Mooney
    Experiments on Ensembles with Missing and Noisy Data. [Citation Graph (0, 0)][DBLP]
    Multiple Classifier Systems, 2004, pp:293-302 [Conf]
  69. Yuk Wah Wong, Raymond J. Mooney
    Learning for Semantic Parsing with Statistical Machine Translation. [Citation Graph (0, 0)][DBLP]
    HLT-NAACL, 2006, pp:- [Conf]
  70. Razvan C. Bunescu, Raymond J. Mooney
    A Shortest Path Dependency Kernel for Relation Extraction. [Citation Graph (0, 0)][DBLP]
    HLT/EMNLP, 2005, pp:- [Conf]
  71. Razvan C. Bunescu, Raymond J. Mooney
    Subsequence Kernels for Relation Extraction. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  72. J. Jeffrey Mahoney, Raymond J. Mooney
    Combining Neural and Symbolic Learning to Revise Probabilistic Rule Bases. [Citation Graph (0, 0)][DBLP]
    NIPS, 1992, pp:107-114 [Conf]
  73. Sugato Basu, Arindam Banerjee, Raymond J. Mooney
    Active Semi-Supervision for Pairwise Constrained Clustering. [Citation Graph (0, 0)][DBLP]
    SDM, 2004, pp:- [Conf]
  74. Dirk Ourston, Raymond J. Mooney
    Theory Refinement Combining Analytical and Empirical Methods. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 1994, v:66, n:2, pp:273-309 [Journal]
  75. Eric Brill, Raymond J. Mooney
    An Overview of Empirical Natural Language Processing. [Citation Graph (0, 0)][DBLP]
    AI Magazine, 1997, v:18, n:4, pp:13-24 [Journal]
  76. Razvan C. Bunescu, Ruifang Ge, Rohit J. Kate, Edward M. Marcotte, Raymond J. Mooney, Arun K. Ramani, Yuk Wah Wong
    Comparative experiments on learning information extractors for proteins and their interactions. [Citation Graph (0, 0)][DBLP]
    Artificial Intelligence in Medicine, 2005, v:33, n:2, pp:139-155 [Journal]
  77. Raymond J. Mooney
    Learning Plan Schemata From Observation: Explanation-Based Learning for Plan Recognition. [Citation Graph (0, 0)][DBLP]
    Cognitive Science, 1990, v:14, n:4, pp:483-509 [Journal]
  78. Raymond J. Mooney
    Comparative Experiments on Disambiguating Word Senses: An Illustration of the Role of Bias in Machine Learning [Citation Graph (0, 0)][DBLP]
    CoRR, 1996, v:0, n:, pp:- [Journal]
  79. Ulf Hermjakob, Raymond J. Mooney
    Learning Parse and Translation Decisions From Examples With Rich Context [Citation Graph (0, 0)][DBLP]
    CoRR, 1997, v:0, n:, pp:- [Journal]
  80. Raymond J. Mooney, Loriene Roy
    Content-Based Book Recommending Using Learning for Text Categorization [Citation Graph (0, 0)][DBLP]
    CoRR, 1999, v:0, n:, pp:- [Journal]
  81. Mikhail Bilenko, Raymond J. Mooney, William W. Cohen, Pradeep Ravikumar, Stephen E. Fienberg
    Adaptive Name Matching in Information Integration. [Citation Graph (0, 0)][DBLP]
    IEEE Intelligent Systems, 2003, v:18, n:5, pp:16-23 [Journal]
  82. Prem Melville, Raymond J. Mooney
    Creating diversity in ensembles using artificial data. [Citation Graph (0, 0)][DBLP]
    Information Fusion, 2005, v:6, n:1, pp:99-111 [Journal]
  83. Paul T. Baffes, Raymond J. Mooney
    Extending Theory Refinement to M-of-N Rules. [Citation Graph (0, 0)][DBLP]
    Informatica (Slovenia), 1993, v:17, n:4, pp:- [Journal]
  84. Cynthia A. Thompson, Raymond J. Mooney
    Acquiring Word-Meaning Mappings for Natural Language Interfaces. [Citation Graph (0, 0)][DBLP]
    J. Artif. Intell. Res. (JAIR), 2003, v:18, n:, pp:1-44 [Journal]
  85. Mary Elaine Califf, Raymond J. Mooney
    Bottom-Up Relational Learning of Pattern Matching Rules for Information Extraction. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2003, v:4, n:, pp:177-210 [Journal]
  86. Claire Cardie, Raymond J. Mooney
    Guest Editors' Introduction: Machine Learning and Natural Language. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1999, v:34, n:1-3, pp:5-9 [Journal]
  87. Raymond J. Mooney
    Encouraging Experimental Results on Learning CNF. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1995, v:19, n:1, pp:79-92 [Journal]
  88. Raymond J. Mooney
    Induction Over the Unexplained: Using Overly-General Domain Theories to Aid Concept Learning. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1993, v:10, n:, pp:79-110 [Journal]
  89. Bradley L. Richards, Raymond J. Mooney
    Automated Refinement of First-Order Horn-Clause Domain Theories. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1995, v:19, n:2, pp:95-131 [Journal]
  90. Mary Elaine Califf, Raymond J. Mooney
    Advantages of Decision Lists and Implicit Negatives in Inductive Logic Programming. [Citation Graph (0, 0)][DBLP]
    New Generation Comput., 1998, v:16, n:3, pp:263-281 [Journal]
  91. Raymond J. Mooney, John M. Zelle
    Integrating ILP and EBL. [Citation Graph (0, 0)][DBLP]
    SIGART Bulletin, 1994, v:5, n:1, pp:12-21 [Journal]
  92. Raymond J. Mooney, Razvan C. Bunescu
    Mining knowledge from text using information extraction. [Citation Graph (0, 0)][DBLP]
    SIGKDD Explorations, 2005, v:7, n:1, pp:3-10 [Journal]
  93. Rohit J. Kate, Raymond J. Mooney
    Learning Language Semantics from Ambiguous Supervision. [Citation Graph (0, 0)][DBLP]
    AAAI, 2007, pp:895-900 [Conf]
  94. Lilyana Mihalkova, Tuyen Huynh, Raymond J. Mooney
    Mapping and Revising Markov Logic Networks for Transfer Learning. [Citation Graph (0, 0)][DBLP]
    AAAI, 2007, pp:608-614 [Conf]
  95. Razvan C. Bunescu, Raymond J. Mooney
    Multiple instance learning for sparse positive bags. [Citation Graph (0, 0)][DBLP]
    ICML, 2007, pp:105-112 [Conf]
  96. Lilyana Mihalkova, Raymond J. Mooney
    Bottom-up learning of Markov logic network structure. [Citation Graph (0, 0)][DBLP]
    ICML, 2007, pp:625-632 [Conf]

  97. Learning to Connect Language and Perception. [Citation Graph (, )][DBLP]


  98. Using Closed Captions as Supervision for Video Activity Recognition. [Citation Graph (, )][DBLP]


  99. Learning Synchronous Grammars for Semantic Parsing with Lambda Calculus. [Citation Graph (, )][DBLP]


  100. Learning to Extract Relations from the Web using Minimal Supervision. [Citation Graph (, )][DBLP]


  101. Fast and Effective Worm Fingerprinting via Machine Learning. [Citation Graph (, )][DBLP]


  102. Learning to sportscast: a test of grounded language acquisition. [Citation Graph (, )][DBLP]


  103. Discriminative structure and parameter learning for Markov logic networks. [Citation Graph (, )][DBLP]


  104. Spherical Topic Models. [Citation Graph (, )][DBLP]


  105. Transfer Learning from Minimal Target Data by Mapping across Relational Domains. [Citation Graph (, )][DBLP]


  106. Generation by Inverting a Semantic Parser that Uses Statistical Machine Translation. [Citation Graph (, )][DBLP]


  107. Semi-Supervised Learning for Semantic Parsing using Support Vector Machines. [Citation Graph (, )][DBLP]


  108. Watch, Listen & Learn: Co-training on Captioned Images and Videos. [Citation Graph (, )][DBLP]


  109. Learning Language from Its Perceptual Context. [Citation Graph (, )][DBLP]


  110. Max-Margin Weight Learning for Markov Logic Networks. [Citation Graph (, )][DBLP]


  111. Learning to Disambiguate Search Queries from Short Sessions. [Citation Graph (, )][DBLP]


  112. Text Mining. [Citation Graph (, )][DBLP]


  113. Transfer Learning by Mapping and Revising Relational Knowledge. [Citation Graph (, )][DBLP]


  114. Induction of First-Order Decision Lists: Results on Learning the Past Tense of English Verbs [Citation Graph (, )][DBLP]


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