02/23/06

Journal Articles
1. R. Feldman and M.C. Golumbic. “Optimization algorithms for scheduling via constraint Satisfiability,” The Computer Journal, pp. 356-364, Aug. 1990. (Expanded version of #5).
2. R. Feldman and M.C. Golumbic. “Interactive scheduling as a constraint satisfiability problem,” In Annals of Mathematics and Artificial Intelligence, pp. 49-73, Aug. 1990 (Expanded version of #6).
3. M. Koppel, R. Feldman and A. Segre “Bias-Driven Revision of Logical Domain Theories,” Journal of Artificial Intelligence Research, pp. 159-208, 1994. (Expanded version of #9,#10,#11)
4. R. Feldman, M. Koppel and A. Segre “Extending the Role of Bias in Probabilistic Theory Revision,” Knowledge Acquisition Journal, Vol. 6, pp. 197-214,1994. (Expanded version of #13)

Conference Proceedings
5. R. Feldman and M.C. Golumbic. “Interactive Scheduling as a Constraint Labeling Problem,” In Proceedings of the 4th Israeli Symposium on Artificial Intelligence, pp. 136-145, December 1987, Ramat-Gan, Israel.
6. R. Feldman and M.C. Golumbic “Constraint Satisfiability algorithms for interactive student scheduling,” In Proceedings of IJCAI-89, pp. 1010-1016, Aug. 1989, Detroit, MI.
7. D. Subramanian and R. Feldman “The Utility of EBL in Recursive Domains,” In Proceedings of AAAI-90, pp. 942-949, July 1990 ,Boston, MA.
8. R. Feldman and D. Subramanian. “Example Guided Optimization of Recursive Domain Theories,” In Proceedings of IEEE AI Applications Conference., pp. 240-244, Feb. 1991, Miami Beach, FL.
9. R. Feldman, A. Segre and M. Koppel. “Incremental Refinement of Approximate Domain Theories,” In Proceedings of the 8th Intl. Machine Learning Conference, pp. 500-504, June 1991 Evanston, IL.
10. R. Feldman, A. Segre and M. Koppel. “Refinement of Approximate Rule Bases,”, In Proceedings of the World Congress on Expert Systems, pp. 615-622, Dec. 1991 Orlando, FL.
11. R. Feldman, M. Koppel and A. Segre “Probabilistic Revision of Logical Domain Theories,” In Working Notes of AAAI Spring Symposium on Knowledge Assimilation, pp. 51-61, March 1992, Stanford, CA.
12. R. Feldman, M. Koppel and A. Segre “Probabilistic Revision of Propositional Domain Theories,” In Proceedings of the 9th Israeli Symposium on Artificial Intelligence, pp. 132-146, December 1992, Ramat-Gan, Israel.
13. R. Feldman, M. Koppel and A. Segre “The Relevance of Bias in the Revision of Approximate Domain Theories,” In Proceedings of IJCAI-93 workshop on Knowledge Acquisition and Machine Learning, pp. 44-60, August 1993, Chambery, France.
14. M. Koppel, R. Feldman and A. Segre “Theory Revision Using Noisy Exemplars,” In Proceedings of the 10th Israeli Symposium on Artificial Intelligence, pp. 96-107, December 1993, Ramat-Gan, Israel.
15. R. Feldman and C. Nedellec “A Framework for Specifying Explicit Bias for Revision of approximate Knowledge Bases,” In Proceedings of the 7th International Conference on Knowledge Acquisition, chapter 15, pp. 1-20, Banff, Canada, Feb 1994.
16. M. Koppel, A. Segre and R. Feldman. “Getting the Most from a Flawed Theory,” 9th International Machine Learning Conference, pp. 139-147, Rutgers, NJ, June 1994.
17. R. Feldman. “FRST - An Interactive Revision System for Forward Chaining Rule Bases,” In Proceedings of ECAI workshop on integration of Knowledge Acquisition and Machine Learning, Amsterdam, Holland, Aug 1994.
18. R. Feldman and I. Dagan. “Knowledge Discovery in Texts,” In Proceedings of the ECML-95 Workshop on Knowledge Discovery, pp. 175-180, Crete, Greece, May 1995.
19. R. Feldman and I. Dagan. “Knowledge Discovery in Textual Databases (KDT),” In Proceedings of the 1st International Conference on Knowledge Discovery (KDD-95), pp. 112-117, Montreal, Aug 1995.
20. S. Engelson, R. Feldman, M. Koppel, A. Nerode, J. Remmel “FROST - A Forward Chaining Rule Ordering System for Reasoning with Nonmonotonic Rule Systems,” In Proceedings of the IJCAI-95 workshop on Implementation of Nonmonotonic Systems, pp. 27-36, Montreal, Aug 1995.

ii. Publications since last promotion
a. Reviewed

Patents
21. Ronen Feldman, Yonatan Aumann, Yonatan Schler, David Landau, Orly Lipshtat, Yaron Ben Yehuda: US Patent 6,442,545, “Term Level Text Mining with Taxonomies”, Aug 27, 2002.
22. Ronen Feldman, Yonatan Aumann, Yaron Ben Yehuda, David Landau: US Patent 6,532,469, “Determining Trends using Text Mining”, Mar 11th, 2003.

Magazine Articles
23. Ronen Feldman, “Unified Business Intelligence: Voices of BI”, DM review, February 2005.
24. Ronen Feldman, “Unified Business Intelligence: Voices from the Next Frontier”, DM review, March 2005.
25. Ronen Feldman, “Unified Business Intelligence: Three Vs: Best Practices for a Unified Business Intelligence Infrastructure”, DM review, April 2005.
26. Ronen Feldman, “Unified Business Intelligence: Managing Risk for the Financial Services Market in a World of Uncertainty”, DM review, June 2005.
27. Ronen Feldman, “Unified Business Intelligence: Defining Alliances in the Post-Unified Business Intelligence World”, DM review, July 2005.
28. Ronen Feldman, “Unified Business Intelligence: UIMA - Is IBM Hearing Voices?”, DM review, August 2005.

Books
29. Ronen Feldman and Jim Sanger. “Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data,” Cambridge University Press, forthcoming 2006.

Book Chapters
30. M. Koppel, A. Segre and R. Feldman. “An Integrated Framework for Knowledge Representation and Theory Revision,” In Machine Learning and Knowledge Acquisition, pp. 95-114, G. Tecuci and Y. Kodratoff (Eds.), Academic Press, 1995. (Expanded version of #12, #15, #16)
31. R. Feldman, I. Dagan, and W. Kloesgen. “KDD Tools for Mining Associations in Textual Databases, ” Springer Lecture Notes in Computer Science, volume 1079, 96-107, 1996.
32. A. Amir, R. Feldman, and R. Kashi. “A New and Versatile Algorithm for Association Generation,” Springer Lecture Notes in Computer Science, volume 1263 , 221-231, 1997.
33. R. Feldman, W. Klösgen, Y. Ben-Yehuda, G. Kedar and V. Reznikov. “Pattern based browsing in document collections,” Springer Lecture Notes in Computer Science, volume 1263, 112-122, 1997.
34. R. Feldman and H. Hirsh. “Finding Associations in Collections of Text, ” In Methods and Applications of Machine Learning, Data Mining and Knowledge Discovery, R.S. Michalski, I. Bratko, and M. Kubat (eds.), John Wiley and Sons, Ltd., 1997, 20 pages. (Expanded version of #24, #27)
35. R. Feldman, W. Kloesgen and A. Zilberstien " Document Explorer: Discovering Knowledge in Document Collections". Springer Lecture Notes in Computer Science, volume 1325, 137-146, 1997.
36. Ronen Feldman, Yonatan Aumann, Amir Zilberstein, Yaron Ben-Yehuda: Trend Graphs: Visualizing the Evolution of Concept Relationships in Large Document Collections. Springer Lecture Notes in Computer Science, volume 1510, 38-46, 1997
37. David Landau, Ronen Feldman, Yonatan Aumann, Moshe Fresko, Yehuda Lindell, Orly Liphstat, Oren Zamir: TextVis: An Integrated Visual Environment for Text Mining. Springer Lecture Notes in Computer Science, volume 1510, 56-64, 1997
38. Ronen Feldman, Moshe Fresko, Yakkov Kinar, Yehuda Lindell, Orly Liphstat, Martin Rajman, Yonatan Schler, Oren Zamir: Text Mining at the Term Level. Springer Lecture Notes in Computer Science, volume 1510, 65-73, 1997.
39. Ronen Feldman, Yonatan Aumann, Moshe Fresko, Orly Lipshtat, Binyamin Rosenfeld, Yonatan Schler: Text Mining via Information Extraction. Springer Lecture Notes in Computer Science, volume 1704, 165-173
40. Yonatan Aumann, Ronen Feldman, Yaron Ben Yehuda, David Landau, Orly Lipshtat, Yonatan Schler: Circle Graphs: New Visualization Tools for Text-Mining. Springer Lecture Notes in Computer Science, volume 1704, 277-282.
41. Ronen Feldman. “Document Explorer”, Part Four, Chapter 24 in the Handbook of Data Mining and Knowledge Discovery, Oxford University Press 2002, 629-636.
42. Ronen Feldman. “Text Mining”, Part Six, Chapter 38 in the Handbook of Data Mining and Knowledge Discovery, Oxford University Press 2002, 749-757.
43. Sundar Varadarajan, Kas Kasravi, Ronen Feldman: Text-Mining: Application Development Challenges. In Proceedings of the Twenty-second SGAI International Conference on Knowledge Based Systems and Applied Artificial Intelligence, December 2002, Applications and Innovations in Intelligent Systems X, Springer-Verlag, 8 pages.
44. Ronen Feldman. “Mining Text Data”, Chapter 21 in Handbook of Data Mining, Lawrence Erlbaum Associates, 2003, 48 pages.
45. Moty Ben-Dov, Ronen Feldman: Text Mining and Information Extraction. The Data Mining and Knowledge Discovery Handbook 2005: 801-831, Springer.

Journal Articles
46. Amihood Amir, Ronen Feldman, Reuven Kashi: A New and Versatile Method for Association Generation. IS 22(6/7): 333-347 (1997)
47. Ronen Feldman, Haym Hirsh: Exploiting Background Information in Knowledge Discovery from Text. JIIS 9(1): 83-97 (1997)
48. Ronen Feldman, Ido Dagan, Haym Hirsh: Mining Text Using Keyword Distributions. JIIS 10(3): 281-300 (1998)
49. Ronen Feldman, Willi Klösgen: Data Mining on the Web: A Promising Challenge? KI 12(1): 35-36 (1998)
50. Yonatan Aumann, Ronen Feldman, Orly Liphstat, Heikki Mannila: Borders: An Efficient Algorithm for Association Generation in Dynamic Databases. JIIS 12(1): 61-73 (1999)
51. Ronen Feldman, Yizhar Regev, Michal Finkelstein-Landau, Eyal Hurvitz & Boris Kogan: Mining biomedical literature using information extraction. Current Drug Discovery, Volume2, Issue 10, pages 19-23,October 2002.
52. Yizhar Regev, Michal Finkelstein-Landau, Ronen Feldman: Using Rule-based Information Extraction for Locating Experimental Evidence in the Biomedical Domain – the KDD Cup 2002. KDD Explorations, December 2002, 3 pages.
53. Ronen Feldman, Josuha Livnat and Ron Lazar: Earnings Guidance after Regulation FD. Journal of Investment, 33 pages.
54. Hagit Shatkay and Ronen Feldman: Mining the Biomedical Literature in the genomic era, a review. Journal of Computational Biology, 10 (6): 821-855 (2003).
55. Ronen Feldman, Yizhar Regev, Michal Finkelstein-Landau, Eyal Hurvitz & Boris Kogan, “Mining the biomedical literature using semantic analysis”, Biosilico 1(2):69-80 (2003).
56. Yonatan Aumann, Amihood Amir, Ronen Feldman, Moshe Fresko, “Maximal Association Rules: a Tool for Mining Associations in Text”, J. Intell. Inf. Syst. 25(3): 333-345 (2005).
57. Ronen Feldman, Benjamin Rosenfeld, Moshe Fresko, “TEG - A Hybrid Approach to Information Extraction”, KAIS, 9(1): 1-18 (2006).
58. Yonatan Aumann, Ronen Feldman, Benjamin Rosenfeld, , Yair Liberzon, Jonathan Schler, “Visual Information Extraction”, accepted to KAIS, 16 pages.
59. Ronen Feldman, Benjamin Rosenfeld, Joshua Livnat, “Reasons for Late SEC Filings: Computerized Retrieval and Classification”, Accepted for publication to Journal of Intelligent Data Analysis, 13 pages.
60. Ronen Feldman, Maya Gorodetzky, Yizhar Regev, “DIAL: A Dedicated Information Extraction Language”, in preparation.

Conference Proceedings
61. R. Feldman, I. Dagan, and W. Kloesgen. “Efficient Algorithms for Mining and Manipulating Associations in Texts, ” In Proceedings of EMCSR96, pp. 949-954, Vienna, Austria, April 1996.
62. Dagan , R. Feldman., and H. Hirsh. “Keyword-Based Browsing and Analysis of Large Document Sets, ” In Proceedings of SDAIR96, pp. 191-208, Las Vegas, Nevada April 1996.
63. R. Feldman, “The KDT System - Using Prolog for KDD, ” In Proceedings of the 4th Conference on Practical Applications of Prolog, pp. 91-110, London, April 1996.
64. R. Feldman and H. Hirsh. “Mining Associations in Text in the Presence of Background Knowledge, ” In Proceedings of the 2nd International Conference on Knowledge Discovery (KDD-96), pp. 343-346, Portland, Aug 1996.
65. R. Feldman, A. Amir, Y. Aumann, A. Zilberstein, and H. Hirsh. “Incremental Algorithms for Association Generation, ” In Proceedings of the 1st Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD97), 14 pages, Singapore, 1997.
66. R. Feldman, Y. Aumann, A. Amir and H. Mannila. “Efficient Algorithms for Discovering Frequent Sets in Incremental Databases”, In SIGMOD’97 Workshop on Research Issues in Data Mining and Knowledge Discovery (DMKD’97), 12 pages, AZ, USA, 1997.
67. R. Feldman, Y. Aumann, A. Amir, W. Kloesgen and A. Zilberstien “Maximal Association Rules: a New Tool for Mining for Keyword co-occurrences in Document Collections”, In Proceedings of the 3rd International Conference on Knowledge Discovery (KDD-97), Newport Beach, 167-170, CA, Aug 1997.
68. R. Feldman, Y. Aumann, A. Amir, W. Kloesgen and A. Zilberstien “Visualization Techniques to Explore Data Mining Results for Document Collections”, In Proceedings of the 3rd International Conference on Knowledge Discovery (KDD-97), 16-23, Newport Beach, CA, Aug 1997.
69. Ronen Feldman: Mining Unstructured Data. KDD Tutorial Notes 1999: 182-236
70. Ronen Feldman, Yair Liberzon, Binyamin Rosenfeld, Jonathan Schler, Jonathan Stoppi: A framework for specifying explicit bias for revision of approximate information extraction rules. KDD 2000: 189-197
71. Ronen Feldman, Yonatan Aumann, Yair Liberzon, Kfir Ankori, Jonathan Schler, Benjamin Rosenfeld: A Domain Independent Environment for Creating Information Extraction Modules. CIKM 2001: 586-588

72. Ronen Feldman, Yonatan Aumann, Michal Finkelstein-Landau, Eyal Hurvitz, Yizhar Regev, Ariel Yaroshevich: A Comparative Study of Information Extraction Strategies. CICLing 2002: 349-359
73. Benjamin Rosenfeld, Ronen Feldman, Yonatan Aumann: Structural Extraction from Visual Layout of Documents. CIKM 2002, 203-210.
74. Benjamin Rosenfeld, Ronen Feldman, Moshe Fresko, Jonathan Schler, Yonatan Aumann: TEG - A Hybrid Approach to Information Extraction, CIKM 2004, 589-596.
75. Ronen Feldman, Benjamin Rosenfeld, Moshe Fresko, Brian Davison, “Hybrid Semantic Tagging for Information Extraction”, WWW’05, Japan, 1022-1023.
76. Benjamin Rosenfeld, Moshe Fresko, Ronen Feldman, A Systematic Comparison of Feature-Rich Probabilistic Classifiers for NER Tasks, PKDD 2005, Lecture Notes in Computer Science, Volume 3721, Nov 2005, Pages 217 – 227
77. Fresko Moshe, Binyamin Rosenfeld, Ronen Feldman. “A Hybrid Approach to NER by MEMM and Manual Rules,”, CIKM, 2005, Bremen, Germany, 361-362.
78. Moshe Fresko, Binyamin Rozenfeld, and Ronen Feldman. “A Hybrid Approach to NER by Integrating Manual Rules into MEMM,” AI and Math 2006, Ft. Lauderdale, Florida, 7 pages.
79. Binyamin Rosenfeld, Ronen Feldman, Fresko Moshe “A Systematic Cross-Comparison of Sequence Classifiers,”, SDM 2006, Maryland, USA, 5 pages.