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Note: Links lead to the DBLP on the Web. Haym Hirsh Sofus A. Macskassy , Haym Hirsh: Adding numbers to text classification. CIKM 2003 : 240-246 Sarah Zelikovitz , Haym Hirsh: Integrating Background Knowledge Into Text Classification. IJCAI 2003 : 1448-1449 Sofus A. Macskassy , Haym Hirsh, Arunava Banerjee , Aynur A. Dayanik : Converting numerical classification into text classification. Artif. Intell. 143 (1): 51-77 (2003) Sarah Zelikovitz , Haym Hirsh: Integrating Background Knowledge into Nearest-Neighbor Text Classification. ECCBR 2002 : 1-5 Steve Chien , Haym Hirsh: Editorial Introduction: The Fourteenth Innovative Applications of Artificial Intelligence Conference (IAAI-2001). AI Magazine 23 (2): 9-10 (2002) Haym Hirsh, Steve Chien : Proceedings of the Thirteenth Innovative Applications of Artificial Intelligence Conference, August 7-9, 2001, Seattle, Washington, USA AAAI 2001 Sarah Zelikovitz , Haym Hirsh: Using LSI for Text Classification in the Presence of Background Text. CIKM 2001 : 113-118 Sofus A. Macskassy , Haym Hirsh, Arunava Banerjee , Aynur A. Dayanik : Using Text Classifiers for Numerical Classification. IJCAI 2001 : 885-890 Sofus A. Macskassy , Haym Hirsh, Foster J. Provost , Ramesh Sankaranarayanan , Vasant Dhar : Intelligent Information Triage. SIGIR 2001 : 318-326 Robert S. Engelmore , Haym Hirsh: Editorial Introduction to this Special Issue of AI Magazine: The Twelfth Innovative Applications of Artificial Intelligence Conference (IAAI-2000). AI Magazine 22 (2): 13-14 (2001) Chumki Basu , Haym Hirsh, William W. Cohen , Craig G. Nevill-Manning : Technical Paper Recommendation: A Study in Combining Multiple Information Sources. JAIR 14 : 231-252 (2001) Gary M. Weiss , Haym Hirsh: A Quantitative Study of Small Disjuncts. AAAI/IAAI 2000 : 665-670 Khaled Rasheed , Haym Hirsh: Informed operators: Speeding up genetic-algorithm-based design optimization using reduced models. GECCO 2000 : 628-635 Sarah Zelikovitz , Haym Hirsh: Improving Short-Text Classification using Unlabeled Data for Classification Problems. ICML 2000 : 1191-1198 Haym Hirsh, Chumki Basu , Brian D. Davison : Enabling technologies: learning to personalize. Commun. ACM 43 (8): 102-106 (2000) Marti A. Hearst , Haym Hirsh: AI's Greatest Trends and Controversies. IEEE Intelligent Systems 15 (1): 8-17 (2000) Daniel Kudenko , Haym Hirsh: Feature-Based Learners for Description Logics. Description Logics 1999 Chumki Basu , Haym Hirsh, William W. Cohen : Recommendation as Classification: Using Social and Content-Based Information in Recommendation. AAAI/IAAI 1998 : 714-720 Daniel Kudenko , Haym Hirsh: Feature Generation for Sequence Categorization. AAAI/IAAI 1998 : 733-738 Gary M. Weiss , Haym Hirsh: The Problem with Noise and Small Disjuncts. ICML 1998 : 574- William W. Cohen , Haym Hirsh: Joins that Generalize: Text Classification Using WHIRL. KDD 1998 : 169-173 Sofus A. Macskassy , Arunava Banerjee , Brian D. Davison , Haym Hirsh: Human Performance on Clustering Web Pages: A Preliminary Study. KDD 1998 : 264-268 Gary M. Weiss , Haym Hirsh: Learning to Predict Rare Events in Event Sequences. KDD 1998 : 359-363 Ronen Feldman , Moshe Fresko , Haym Hirsh, Yonatan Aumann , Orly Liphstat , Yonatan Schler , Martin Rajman : Knowledge Management: A Text Mining Approach. PAKM 1998 Haym Hirsh: Trends & Controversies: Interactive Fiction. IEEE Intelligent Systems 13 (6): 12-21 (1998) Ronen Feldman , Ido Dagan , Haym Hirsh: Mining Text Using Keyword Distributions. J. Intell. Inf. Syst. 10 (3): 281-300 (1998) Haym Hirsh, Daniel Kudenko : Representing Sequences in Description Logics. AAAI/IAAI 1997 : 384-389 Haym Hirsh, Nina Mishra , Leonard Pitt : Version Spaces without Boundary Sets. AAAI/IAAI 1997 : 491-496 Brian D. Davison , Haym Hirsh: Experiments in UNIX Command Prediction. AAAI/IAAI 1997 : 827 Haym Hirsh, Brian D. Davison : An Adaptive UNIX Command-Line Assistant. Agents 1997 : 542-543 Brian D. Davison , Haym Hirsh: Toward an Adaptive Command Line Interface. HCI (2) 1997 : 505-508 Khaled Rasheed , Haym Hirsh: Using Case Based Learning to Improve Genetic Algorithm Based Design Optimization. ICGA 1997 : 513-520 Ronen Feldman , Haym Hirsh: Exploiting Background Information in Knowledge Discovery from Text. J. Intell. Inf. Syst. 9 (1): 83-97 (1997) Daniel Kudenko , Haym Hirsh: Representing Sequences in Description Logics Using Suffix Trees. Description Logics 1996 : 141-145 Ronen Feldman , Haym Hirsh: Mining Associations in Text in the Presence of Background Knowledge. KDD 1996 : 343-346 Kwong Bor Ng , David Loewenstern , Chumki Basu , Haym Hirsh, Paul B. Kantor : Data Fusion of Machine-Learning Methods for the TREC5 Routing Task (and other work). TREC 1996 William W. Cohen , Haym Hirsh: Corrigendum for ``Learnability of Description Logics''. COLT 1995 : 463 Haym Hirsh, Nathalie Japkowicz : Bootstrapping Training-Data Representations for Inductive Learning: A Case Study in Molecular Biology. AAAI 1994 : 639-644 William W. Cohen , Haym Hirsh: Learning the Classic Description Logic: Theoretical and Experimental Results. KR 1994 : 121-133 Haym Hirsh, Michiel O. Noordewier : Using Background Knowledge to Improve Inductive Learning: A Case Study in Molecular Biology. IEEE Expert 9 (5): 3-6 (1994) Haym Hirsh: Generalizing Version Spaces. Machine Learning 17 (1): 5-46 (1994) William W. Cohen , Haym Hirsh: The Learnability of Description Logics with Equality Constraints. Machine Learning 17 (2-3): 169-199 (1994) Steven W. Norton , Haym Hirsh: Learning DNF Via Probabilistic Evidence Combination. ICML 1993 : 220-227 Haym Hirsh: Polynomial-Time Learning with Version Spaces. AAAI 1992 : 117-122 Steven W. Norton , Haym Hirsh: Classifier Learning from Noisy Data as Probabilistic Evidence Combination. AAAI 1992 : 141-146 William W. Cohen , Alexander Borgida , Haym Hirsh: Computing Least Common Subsumers in Description Logics. AAAI 1992 : 754-760 William W. Cohen , Haym Hirsh: Learnability of Description Logics. COLT 1992 : 116-127 Haym Hirsh: Theoretical Underpinnings of Version Spaces. IJCAI 1991 : 665-670 Haym Hirsh: Learning from Data with Bounded Inconsistency. ML 1990 : 32-39 Haym Hirsh: Incremental Version-Space Merging. ML 1990 : 330-338 Melissa P. Chase , Monte Zweben , Richard L. Piazza , John D. Burger , Paul P. Maglio , Haym Hirsh: Approximating Learned Search Control Knowledge. ML 1989 : 218-220 Haym Hirsh: Combining Empirical and Analytical Learning with Version Spaces. ML 1989 : 29-33 Scott H. Clearwater , Tze-Pin Chen , Haym Hirsh, Bruce G. Buchanan : Incremental Batch Learning. ML 1989 : 366-370 Haym Hirsh: Reasoning about Operationality for Explanation-Based Learning. ML 1988 : 214-220 Haym Hirsh: Explanation-based Generalization in a Logic- Programming Environment. IJCAI 1987 : 221-227 1 [ 32 ] 2 [ 34 ] [ 48 ] [ 53 ] 3 [ 20 ] [ 38 ] [ 41 ] [ 45 ] 4 [ 10 ] 5 [ 3 ] 6 [ 5 ] 7 [ 5 ] 8 [ 3 ] 9 [ 50 ] [ 51 ] 10 [ 3 ] 11 [ 9 ] [ 10 ] [ 14 ] [ 17 ] [ 19 ] [ 35 ] [ 38 ] [ 45 ] 12 [ 30 ] 13 [ 25 ] [ 26 ] [ 27 ] [ 34 ] [ 41 ] 14 [ 48 ] [ 53 ] 15 [ 47 ] 16 [ 46 ] 17 [ 21 ] [ 23 ] [ 30 ] [ 32 ] 18 [ 32 ] 19 [ 40 ] 20 [ 18 ] 21 [ 20 ] 22 [ 22 ] [ 29 ] [ 37 ] [ 39 ] 23 [ 32 ] 24 [ 20 ] 25 [ 34 ] [ 47 ] [ 48 ] [ 53 ] [ 55 ] 26 [ 5 ] 27 [ 28 ] 28 [ 45 ] 29 [ 20 ] 30 [ 16 ] 31 [ 11 ] [ 13 ] 32 [ 5 ] 33 [ 28 ] 34 [ 47 ] 35 [ 32 ] 36 [ 24 ] [ 43 ] 37 [ 47 ] 38 [ 32 ] 39 [ 33 ] [ 36 ] [ 44 ] 40 [ 42 ] [ 49 ] [ 52 ] [ 54 ] 41 [ 5 ]  ©2004 Association for Computing Machinery |
