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Stan Matwin: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Svetlana Kiritchenko, Stan Matwin
    Generalized Features: Their Application to Classification. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 2002, pp:985- [Conf]
  2. Sylvain Delisle, Sylvain Létourneau, Stan Matwin
    Experiments with Learning Parsing Heuristics. [Citation Graph (0, 0)][DBLP]
    COLING-ACL, 1998, pp:307-314 [Conf]
  3. Daniel Charlebois, David G. Goodenough, Stan Matwin, A. S. (Pal) Bhogal, Hugh Barclay
    Planning and Learning in a Natural Resource Information System. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 1996, pp:187-199 [Conf]
  4. Quintin Armour, William Elazmeh, Nour El-Kadri, Nathalie Japkowicz, Stan Matwin
    Privacy Compliance Enforcement in Email. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 2005, pp:194-204 [Conf]
  5. Maria Fernanda Caropreso, Stan Matwin
    Beyond the Bag of Words: A Text Representation for Sentence Selection. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 2006, pp:324-335 [Conf]
  6. Ouerd Messaouda, B. John Oommen, Stan Matwin
    Enhancing Caching in Distributed Databases Using Intelligent Polytree Representations. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 2003, pp:498-504 [Conf]
  7. Johanne Morin, Stan Matwin
    Relational Learning with Transfer of Knowledge Between Domains. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 2000, pp:379-388 [Conf]
  8. David Nadeau, Peter D. Turney, Stan Matwin
    Unsupervised Named-Entity Recognition: Generating Gazetteers and Resolving Ambiguity. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 2006, pp:266-277 [Conf]
  9. Svetlana Kiritchenko, Stan Matwin, Richard Nock, A. Fazel Famili
    Learning and Evaluation in the Presence of Class Hierarchies: Application to Text Categorization. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 2006, pp:395-406 [Conf]
  10. Riverson Rios, Stan Matwin
    Efficient Induction of Recursive Prolog Definitons. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 1996, pp:240-248 [Conf]
  11. Riverson Rios, Stan Matwin
    Predicate Invention from a Few Examples. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 1998, pp:455-466 [Conf]
  12. Marvin Zaluski, Nathalie Japkowicz, Stan Matwin
    Case Authoring from Text and Historical Experiences. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 2003, pp:222-236 [Conf]
  13. Guillaume Dufay, Amy P. Felty, Stan Matwin
    Privacy-Sensitive Information Flow with JML. [Citation Graph (0, 0)][DBLP]
    CADE, 2005, pp:116-130 [Conf]
  14. Kenneth Forsythe, Stan Matwin
    Implementation Strategies for Plan-Based Deduction. [Citation Graph (0, 0)][DBLP]
    CADE, 1984, pp:426-444 [Conf]
  15. Stan Matwin, Tomasz Pietrzykowski
    Exponential Improvement of Efficient Backtracking: data Structure and Implementation. [Citation Graph (0, 0)][DBLP]
    CADE, 1982, pp:240-259 [Conf]
  16. Tomasz Pietrzykowski, Stan Matwin
    Exponential Improvement of Efficient Backtracking: A Strategy for Plan-Based Deduction. [Citation Graph (0, 0)][DBLP]
    CADE, 1982, pp:223-239 [Conf]
  17. Svetlana Kiritchenko, Stan Matwin
    Email classification with co-training. [Citation Graph (0, 0)][DBLP]
    CASCON, 2001, pp:8- [Conf]
  18. Jelber Sayyad-Shirabad, Timothy C. Lethbridge, Stan Matwin
    Supporting maintenance of legacy software with data mining techniques. [Citation Graph (0, 0)][DBLP]
    CASCON, 2000, pp:11- [Conf]
  19. Jelber Sayyad-Shirabad, Timothy C. Lethbridge, Stan Matwin
    Applying data mining to software maintenance records. [Citation Graph (0, 0)][DBLP]
    CASCON, 2003, pp:253-265 [Conf]
  20. Narjès Boufaden, William Elazmeh, Yimin Ma, Stan Matwin, Nour El-Kadri, Nathalie Japkowicz
    PEEP- An Information Extraction base approach for Privacy Protection in Email. [Citation Graph (0, 0)][DBLP]
    CEAS, 2005, pp:- [Conf]
  21. Justin Z. Zhan, LiWu Chang, Stan Matwin
    Privacy-Preserving Multi-Party Decision Tree Induction. [Citation Graph (0, 0)][DBLP]
    DBSec, 2004, pp:341-355 [Conf]
  22. Justin Z. Zhan, Stan Matwin, LiWu Chang
    Privacy-Preserving Collaborative Association Rule Mining. [Citation Graph (0, 0)][DBLP]
    DBSec, 2005, pp:153-165 [Conf]
  23. Gregory E. Kersten, Stan Matwin, Sunil J. Noronha, Mik Kersten
    The Software for Cultures and the Cultures in Software. [Citation Graph (0, 0)][DBLP]
    ECIS, 2000, pp:- [Conf]
  24. Sylvain Delisle, Stan Matwin, Lionel Zupan
    Integrating EBL with automatic Text Analysis. [Citation Graph (0, 0)][DBLP]
    EWSL, 1991, pp:347- [Conf]
  25. David W. Aha, Stephane Lapointe, Charles X. Ling, Stan Matwin
    Inverting Implication with Small Training Sets. [Citation Graph (0, 0)][DBLP]
    ECML, 1994, pp:31-48 [Conf]
  26. Francesco Bergadano, Stan Matwin, Ryszard S. Michalski, Jianping Zhang
    Measuring Quality of Concept Descriptions. [Citation Graph (0, 0)][DBLP]
    EWSL, 1988, pp:1-14 [Conf]
  27. Peter Clark, Stan Matwin
    Learning Domain Theories using Abstract Beckground Knowledge. [Citation Graph (0, 0)][DBLP]
    ECML, 1993, pp:360-365 [Conf]
  28. William Elazmeh, Nathalie Japkowicz, Stan Matwin
    Evaluating Misclassifications in Imbalanced Data. [Citation Graph (0, 0)][DBLP]
    ECML, 2006, pp:126-137 [Conf]
  29. Miroslav Kubat, Robert C. Holte, Stan Matwin
    Learning When Negative Examples Abound. [Citation Graph (0, 0)][DBLP]
    ECML, 1997, pp:146-153 [Conf]
  30. Sylvain Létourneau, Stan Matwin, Fazel Famili
    A Normalization Method for Contextual Data: Experience from a Large-Scale Application. [Citation Graph (0, 0)][DBLP]
    ECML, 1998, pp:49-54 [Conf]
  31. Justin Z. Zhan, Stan Matwin
    A Crypto-Based Approach to Privacy-Preserving Collaborative Data Mining. [Citation Graph (0, 0)][DBLP]
    ICDM Workshops, 2006, pp:546-550 [Conf]
  32. Justin Z. Zhan, LiWu Chang, Stan Matwin
    Bayesian Network Induction With Incomplete Private Data. [Citation Graph (0, 0)][DBLP]
    ICEB, 2004, pp:1119-1124 [Conf]
  33. Justin Z. Zhan, Stan Matwin
    Privacy-Preserving Data Mining in Electronic Surveys. [Citation Graph (0, 0)][DBLP]
    ICEB, 2004, pp:1179-1185 [Conf]
  34. Justin Z. Zhan, Stan Matwin, Nathalie Japkowicz, LiWu Chang
    Privacy-Preserving Collaborative Association Rule Mining. [Citation Graph (0, 0)][DBLP]
    ICEB, 2004, pp:1172-1178 [Conf]
  35. David W. Aha, Stephane Lapointe, Charles X. Ling, Stan Matwin
    Learning Recursive Relations with Randomly Selected Small Training Sets. [Citation Graph (0, 0)][DBLP]
    ICML, 1994, pp:12-18 [Conf]
  36. Érick Alphonse, Stan Matwin
    Feature Subset Selection and Inductive Logic Programming. [Citation Graph (0, 0)][DBLP]
    ICML, 2002, pp:11-18 [Conf]
  37. Peter Clark, Stan Matwin
    Using Qualitative Models to Guide Inductive Learning. [Citation Graph (0, 0)][DBLP]
    ICML, 1993, pp:49-56 [Conf]
  38. Jean Genest, Stan Matwin, Boris Plante
    Explanation-Based Learning with Incomplete Theories: A Three-step Approach. [Citation Graph (0, 0)][DBLP]
    ML, 1990, pp:286-294 [Conf]
  39. Mary Gick, Stan Matwin
    The Importance of Causal Structure and Facts in Evaluating Explanations. [Citation Graph (0, 0)][DBLP]
    ML, 1991, pp:51-54 [Conf]
  40. Miroslav Kubat, Stan Matwin
    Addressing the Curse of Imbalanced Training Sets: One-Sided Selection. [Citation Graph (0, 0)][DBLP]
    ICML, 1997, pp:179-186 [Conf]
  41. Stephane Lapointe, Stan Matwin
    Sub-unification: A Tool for Efficient Induction of Recursive Programs. [Citation Graph (0, 0)][DBLP]
    ML, 1992, pp:273-281 [Conf]
  42. Stan Matwin, Johanne Morin
    Learning Procedural Knowledge in the EBG Context. [Citation Graph (0, 0)][DBLP]
    ML, 1989, pp:197-199 [Conf]
  43. Sam Scott, Stan Matwin
    Feature Engineering for Text Classification. [Citation Graph (0, 0)][DBLP]
    ICML, 1999, pp:379-388 [Conf]
  44. Stan Matwin, Affa Ahmad
    Reuse of Modular Software with Automated Comment Analysis. [Citation Graph (0, 0)][DBLP]
    ICSM, 1994, pp:222-231 [Conf]
  45. Jelber Sayyad-Shirabad, Timothy Lethbridge, Stan Matwin
    Mining the Maintenance History of a Legacy Software System. [Citation Graph (0, 0)][DBLP]
    ICSM, 2003, pp:95-104 [Conf]
  46. J. Shirabad, Timothy Lethbridge, Stan Matwin
    Supporting Software Maintenance by Mining Software Update Records. [Citation Graph (0, 0)][DBLP]
    ICSM, 2001, pp:22-31 [Conf]
  47. R. Jetzelsperger, Stan Matwin, Franz Oppacher
    Enhancing Reuse of Smalltalk Methods by Conceptual Clustering. [Citation Graph (0, 0)][DBLP]
    ICTAI, 1993, pp:108-112 [Conf]
  48. Stan Matwin, Stan Szpakowicz, Zbig Koperczak
    NEGOPLAN: An Inference-Based Negotiation Support Tool. [Citation Graph (0, 0)][DBLP]
    IFIP Congress, 1989, pp:679-685 [Conf]
  49. Svetlana Kiritchenko, Stan Matwin, Suhayya Abu-Hakima
    Email Classification with Temporal Features. [Citation Graph (0, 0)][DBLP]
    Intelligent Information Systems, 2004, pp:523-533 [Conf]
  50. Stephane Lapointe, Charles X. Ling, Stan Matwin
    Constructive Inductive Logic Programming. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1993, pp:1030-1036 [Conf]
  51. Xiaobin Li, Stan Szpakowicz, Stan Matwin
    A WordNet-based Algorithm for Word Sense Disambiguation. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1995, pp:1368-1374 [Conf]
  52. Justin Z. Zhan, Stan Matwin, LiWu Chang
    Private Mining of Association Rules. [Citation Graph (0, 0)][DBLP]
    ISI, 2005, pp:72-80 [Conf]
  53. Mauricio Amaral de Almeida, Stan Matwin
    Machine Learning Method for Software Quality Model Building. [Citation Graph (0, 0)][DBLP]
    ISMIS, 1999, pp:565-573 [Conf]
  54. Érick Alphonse, Stan Matwin
    A Dynamic Approach to Dimensionality Reduction in Relational Learning. [Citation Graph (0, 0)][DBLP]
    ISMIS, 2002, pp:255-264 [Conf]
  55. Francesco Bergadano, Stan Matwin, Ryszard S. Michalski, Jianping Zhang
    Representing and Acquiring Imprecise and Context-dependent Concepts in Knowledge-Based Systems. [Citation Graph (0, 0)][DBLP]
    ISMIS, 1988, pp:270-280 [Conf]
  56. Sylvain Delisle, Stan Matwin, Jiandong Wang, Lionel Zupan
    Explanation-based Learning Helps Acquire Knowledge from Natural Language Texts. [Citation Graph (0, 0)][DBLP]
    ISMIS, 1991, pp:326-337 [Conf]
  57. Johanne Morin, Stan Matwin
    Learning Relational Clichés with Contextual LGG. [Citation Graph (0, 0)][DBLP]
    ISMIS, 2000, pp:274-282 [Conf]
  58. Stan Matwin, Franz Oppacher
    Learning by Watching: An Incremental Machine Learning Method that Acquires Rules by Conceptual Clustering. [Citation Graph (0, 0)][DBLP]
    ISMIS, 1988, pp:363-373 [Conf]
  59. M. Ouerd, B. John Oommen, Stan Matwin
    A Formalism for Building Causal Polytree Structures Using Data Distributions. [Citation Graph (0, 0)][DBLP]
    ISMIS, 2000, pp:629-637 [Conf]
  60. Amy P. Felty, Stan Matwin
    Privacy-Oriented Data Mining by Proof Checking. [Citation Graph (0, 0)][DBLP]
    PKDD, 2002, pp:138-149 [Conf]
  61. Jerffeson Teixeira de Souza, Nathalie Japkowicz, Stan Matwin
    STochFS: A Framework for Combining Feature Selection Outcomes Through a Stochastic Process. [Citation Graph (0, 0)][DBLP]
    PKDD, 2005, pp:667-674 [Conf]
  62. Narjès Boufaden, William Elazmeh, Stan Matwin, Nathalie Japkowicz
    PEEP- Privacy Enforcement in Email Project. [Citation Graph (0, 0)][DBLP]
    PST, 2005, pp:- [Conf]
  63. Stan Matwin, Stan Szpakowicz, Gregory E. Kersten, Wojtek Michalowski, Zbig Koperczak
    A Logic-Based Tools for Negotiation Support. [Citation Graph (0, 0)][DBLP]
    SLP, 1987, pp:499-506 [Conf]
  64. Stan Matwin, Amy P. Felty, István T. Hernádvölgyi, Venanzio Capretta
    Privacy in Data Mining Using Formal Methods. [Citation Graph (0, 0)][DBLP]
    TLCA, 2005, pp:278-292 [Conf]
  65. Jelber Sayyad-Shirabad, Stan Matwin, Timothy C. Lethbridge
    Predictive Software Models. [Citation Graph (0, 0)][DBLP]
    STEP, 2004, pp:10-22 [Conf]
  66. Justin Z. Zhan, LiWu Chang, Stan Matwin
    Building k-nearest neighbor classifiers on vertically partitioned private data. [Citation Graph (0, 0)][DBLP]
    GrC, 2005, pp:708-711 [Conf]
  67. Chris Drummond, Stan Matwin, Chad Gaffield
    Inferring and revising theories with confidence: analyzing bilingualism in the 1901 canadian census. [Citation Graph (0, 0)][DBLP]
    Applied Artificial Intelligence, 2006, v:20, n:1, pp:1-33 [Journal]
  68. Jerffeson Teixeira de Souza, Stan Matwin, Nathalie Japkowicz
    Parallelizing Feature Selection. [Citation Graph (0, 0)][DBLP]
    Algorithmica, 2006, v:45, n:3, pp:433-456 [Journal]
  69. Stan Matwin, Franz Oppacher, Patrick Constant
    Knowledge acquisition by incremental learning from problem-solution pairs. [Citation Graph (0, 0)][DBLP]
    Computational Intelligence, 1989, v:5, n:, pp:58-66 [Journal]
  70. Stan Matwin, Tomasz Pietrzykowski
    Prograph: A Preliminary Report. [Citation Graph (0, 0)][DBLP]
    Comput. Lang., 1985, v:10, n:2, pp:91-126 [Journal]
  71. Douglas R. Skuce, Stan Matwin, Branka Tauzovich, Franz Oppacher, Stan Szpakowicz
    A Logic-Based Knowledge Source System for Natural Language Document. [Citation Graph (0, 0)][DBLP]
    Data Knowl. Eng., 1985, v:1, n:3, pp:201-231 [Journal]
  72. C. Geldrez, Stan Matwin, Johanne Morin, Robert L. Probert
    An Application of Explanation-Based Learning to Protocol Conformance Testing. [Citation Graph (0, 0)][DBLP]
    IEEE Expert, 1990, v:5, n:5, pp:45-60 [Journal]
  73. Cindy L. Mason, Stan Matwin
    Guest Editors' Introduction: Environmental Applications of AI. [Citation Graph (0, 0)][DBLP]
    IEEE Expert, 1995, v:10, n:6, pp:12-13 [Journal]
  74. Stan Matwin, Daniel Charlebois, David G. Goodenough, A. S. (Pal) Bhogal
    Machine Learning and Planning for Data Management in Forestry. [Citation Graph (0, 0)][DBLP]
    IEEE Expert, 1995, v:10, n:6, pp:35-40 [Journal]
  75. Peter Clark, Cao Feng, Stan Matwin, Ko Fung
    Improving Image Classification by Combining Statistical, Case-Based and Model Based Prediction Methods. [Citation Graph (0, 0)][DBLP]
    Fundam. Inform., 1997, v:30, n:3/4, pp:227-240 [Journal]
  76. Stan Matwin
    On the Completeness of a Set of Transformations Optimizing Linear Programs. [Citation Graph (0, 0)][DBLP]
    Inf. Process. Lett., 1977, v:6, n:5, pp:165-167 [Journal]
  77. Stan Matwin
    An Experimental Investigation of Geschke's Method of Global Program Optimization. [Citation Graph (0, 0)][DBLP]
    Inf. Process. Lett., 1977, v:6, n:6, pp:177-179 [Journal]
  78. M. Ouerd, B. John Oommen, Stan Matwin
    A formal approach to using data distributions for building causal polytree structures. [Citation Graph (0, 0)][DBLP]
    Inf. Sci., 2004, v:168, n:1-4, pp:111-132 [Journal]
  79. Érick Alphonse, Stan Matwin
    Filtering Multi-Instance Problems to Reduce Dimensionality in Relational Learning. [Citation Graph (0, 0)][DBLP]
    J. Intell. Inf. Syst., 2004, v:22, n:1, pp:23-40 [Journal]
  80. Gilles Fouqué, Stan Matwin
    A Case-Based Approach to Software Reuse. [Citation Graph (0, 0)][DBLP]
    J. Intell. Inf. Syst., 1993, v:2, n:2, pp:165-197 [Journal]
  81. Miroslav Kubat, Robert C. Holte, Stan Matwin
    Machine Learning for the Detection of Oil Spills in Satellite Radar Images. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1998, v:30, n:2-3, pp:195-215 [Journal]
  82. Stan Matwin
    Guest Editorial. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2004, v:57, n:3, pp:203-204 [Journal]
  83. Patrick Constant, Stan Matwin, Franz Oppacher
    LEW: Learning by Watching. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 1990, v:12, n:3, pp:294-308 [Journal]
  84. Kenneth Forsythe, Stan Matwin
    Copying of Dynamic Structures in a Pascal Environment. [Citation Graph (0, 0)][DBLP]
    Softw., Pract. Exper., 1986, v:16, n:4, pp:335-340 [Journal]
  85. Johanne Morin, Stan Matwin
    GENEX: a tool for testing in ILP. [Citation Graph (0, 0)][DBLP]
    Softw., Pract. Exper., 2001, v:31, n:10, pp:1003-1023 [Journal]
  86. Justin Zhan, Stan Matwin, LiWu Chang
    Privacy-preserving collaborative association rule mining. [Citation Graph (0, 0)][DBLP]
    J. Network and Computer Applications, 2007, v:30, n:3, pp:1216-1227 [Journal]

  87. Strategies for Reducing Risks of Inconsistencies in Access Control Policies. [Citation Graph (, )][DBLP]


  88. Improving Bayesian Learning Using Public Knowledge. [Citation Graph (, )][DBLP]


  89. Active Learning with Automatic Soft Labeling for Induction of Decision Trees. [Citation Graph (, )][DBLP]


  90. Cost-Based Sampling of Individual Instances. [Citation Graph (, )][DBLP]


  91. Classifying Biomedical Abstracts Using Committees of Classifiers and Collective Ranking Techniques. [Citation Graph (, )][DBLP]


  92. Annotation Concept Synthesis and Enrichment Analysis. [Citation Graph (, )][DBLP]


  93. Offensive Language Detection Using Multi-level Classification. [Citation Graph (, )][DBLP]


  94. Robustness of Classifiers to Changing Environments. [Citation Graph (, )][DBLP]


  95. A Concept-Based Framework for Retrieving Evidence to Support Emergency Physician Decision Making at the Point of Care. [Citation Graph (, )][DBLP]


  96. A Cryptographic Solution for Private Distributed Simple Meeting Scheduling. [Citation Graph (, )][DBLP]


  97. Formal correctness of conflict detection for firewalls. [Citation Graph (, )][DBLP]


  98. Classification of Dreams Using Machine Learning. [Citation Graph (, )][DBLP]


  99. Using Secondary Knowledge to Support Decision Tree Classification of Retrospective Clinical Data. [Citation Graph (, )][DBLP]


  100. Privacy and Data Mining: New Developments and Challenges. [Citation Graph (, )][DBLP]


  101. Parameterized Contrast in Second Order Soft Co-occurrences: A Novel Text Representation Technique in Text Mining and Knowledge Extraction. [Citation Graph (, )][DBLP]


  102. Image Analysis and Machine Learning: How to Foster a Stronger Connection? [Citation Graph (, )][DBLP]


  103. Discriminative parameter learning for Bayesian networks. [Citation Graph (, )][DBLP]


  104. Generation of Globally Relevant Continuous Features for Classification. [Citation Graph (, )][DBLP]


  105. Proper Model Selection with Significance Test. [Citation Graph (, )][DBLP]


  106. Improving Co-training with Agreement-Based Sampling. [Citation Graph (, )][DBLP]


  107. A Non-technical User-Oriented Display Notation for XACML Conditions. [Citation Graph (, )][DBLP]


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