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Note: Links lead to the DBLP on the Web. Eric Brill Radu Soricut , Eric Brill: Automatic question answering using the web: Beyond the Factoid. Inf. Retr. 9 (2): 191-206 (2006) Eugene Agichtein , Silviu Cucerzan , Eric Brill: Analysis of factoid questions for effective relation extraction. SIGIR 2005 : 567-568 Radu Soricut , Eric Brill: A Unified Framework For Automatic Evaluation Using 4-Gram Co-occurrence Statistics. ACL 2004 : 613-620 Radu Soricut , Eric Brill: Automatic Question Answering: Beyond the Factoid. HLT-NAACL 2004 : 57-64 Wensi Xi , Jesper Lind , Eric Brill: Learning effective ranking functions for newsgroup search. SIGIR 2004 : 394-401 Raman Chandrasekar , Harr Chen , Simon Corston-Oliver , Eric Brill: Subwebs for specialized search. SIGIR 2004 : 480-481 David Azari , Eric Horvitz , Susan T. Dumais , Eric Brill: Actions, answers, and uncertainty: a decision-making perspective on Web-based question answering. Inf. Process. Manage. 40 (5): 849-868 (2004) Eric Brill: Processing Natural Language without Natural Language Processing. CICLing 2003 : 360-369 David Azari , Eric Horvitz , Susan T. Dumais , Eric Brill: Web-Based Question Answering: A Decision-Making Perspective. UAI 2003 : 11-19 Susan T. Dumais , Michele Banko , Eric Brill, Jimmy J. Lin , Andrew Y. Ng : Web question answering: is more always better?. SIGIR 2002 : 291-298 Michele Banko , Eric Brill: Scaling to Very Very Large Corpora for Natural Language Disambiguation. ACL 2001 : 26-33 Eric Brill, Gary Kacmarcik , Chris Brockett : Automatically Harvesting Katakana-English Term Pairs from Search Engine Query Logs. NLPRS 2001 : 393-399 Eric Brill, Jimmy J. Lin , Michele Banko , Susan T. Dumais , Andrew Y. Ng : Data-Intensive Question Answering. TREC 2001 Eric Brill, Grace Ngai : Man [and Woman] vs. Machine: A Case Study in Base Noun Phrase Learning CoRR cs.CL/0105002 : (2001) Eric Brill, Robert C. Moore : An Improved Error Model for Noisy Channel Spelling Correction. ACL 2000 John C. Henderson , Eric Brill: Bagging and Boosting a Treebank Parser. ANLP 2000 : 34-41 John C. Henderson , Eric Brill: Exploiting Diversity in Natural Language Processing: Combining Parsers CoRR cs.CL/0006003 : (2000) John C. Henderson , Eric Brill: Bagging and Boosting a Treebank Parser CoRR cs.CL/0006011 : (2000) Lidia Mangu , Eric Brill, Andreas Stolcke : Finding consensus in speech recognition: word error minimization and other applications of confusion networks CoRR cs.CL/0010012 : (2000) Eric Brill, Grace Ngai : Man* vs. Machine: A Case Study in Base Noun Phrase Learning. ACL 1999 Eric Brill: A Closer Look at the Automatic Induction of Linguistic Knowledge. Learning Language in Logic 1999 : 49-56 Eric Brill, Radu Florian , John C. Henderson , Lidia Mangu : Beyond N-Grams: Can Linguistic Sophistication Improve Language Modeling? COLING-ACL 1998 : 186-190 Eric Brill, Jun Wu : Classifier Combination for Improved Lexical Disambiguation. COLING-ACL 1998 : 191-195 Lidia Mangu , Eric Brill: Automatic Rule Acquisition for Spelling Correction. ICML 1997 : 187-194 Eric Brill, Raymond J. Mooney : An Overview of Empirical Natural Language Processing. AI Magazine 18 (4): 13-24 (1997) Giorgio Satta , Eric Brill: Efficient Transformation-Based Parsing. ACL 1996 : 255-262 Eric Brill: Transformation-Based Error-Driven Learning and Natural Language Processing: A Case Study in Part-of-Speech Tagging. Computational Linguistics 21 (4): 543-565 (1995) Eric Brill: Some Advances in Transformation-Based Part of Speech Tagging. AAAI 1994 : 722-727 Eric Brill, Philip Resnik : A Rule-Based Approach to Prepositional Phrase Attachment Disambiguation. COLING 1994 : 1198-1204 Eric Brill: Automatic Grammar Induction and Parsing Free Text: A Transformation-Based Approach. ACL 1993 : 259-265 Eric Brill: A Simple Rule-Based Part of Speech Tagger. ANLP 1992 : 152-155 Eric Brill: Discovering the Lexical Features of a Language. ACL 1991 : 339-340 1 [ 31 ] 2 [ 24 ] [ 26 ] 3 [ 20 ] [ 22 ] [ 23 ] 4 [ 21 ] 5 [ 27 ] 6 [ 27 ] 7 [ 27 ] 8 [ 31 ] 9 [ 20 ] [ 23 ] [ 24 ] [ 26 ] 10 [ 11 ] 11 [ 11 ] [ 15 ] [ 16 ] [ 17 ] 12 [ 24 ] [ 26 ] 13 [ 21 ] 14 [ 20 ] [ 23 ] 15 [ 28 ] 16 [ 9 ] [ 11 ] [ 14 ] 17 [ 8 ] 18 [ 18 ] 19 [ 20 ] [ 23 ] 20 [ 13 ] [ 19 ] 21 [ 4 ] 22 [ 7 ] 23 [ 29 ] [ 30 ] [ 32 ] 24 [ 14 ] 25 [ 10 ] 26 [ 28 ]  ©2006 Association for Computing Machinery |
