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» Training a Natural Language Generator From Unaligned Data
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JASIS
2000
143views more  JASIS 2000»
15 years 3 months ago
Discovering knowledge from noisy databases using genetic programming
s In data mining, we emphasize the need for learning from huge, incomplete and imperfect data sets (Fayyad et al. 1996, Frawley et al. 1991, Piatetsky-Shapiro and Frawley, 1991). T...
Man Leung Wong, Kwong-Sak Leung, Jack C. Y. Cheng
141
Voted
ACL
2007
15 years 5 months ago
Guiding Semi-Supervision with Constraint-Driven Learning
Over the last few years, two of the main research directions in machine learning of natural language processing have been the study of semi-supervised learning algorithms as a way...
Ming-Wei Chang, Lev-Arie Ratinov, Dan Roth
HICSS
2003
IEEE
118views Biometrics» more  HICSS 2003»
15 years 9 months ago
Lessons Learned from Real DSL Experiments
Over the years, our group, led by Bob Balzer, designed and implemented three domain-specific languages for use by outside people in real situations. The first language described t...
David S. Wile
124
Voted
WWW
2007
ACM
16 years 4 months ago
Learning information intent via observation
Workers in organizations frequently request help from assistants by sending request messages that express information intent: an intention to update data in an information system....
Anthony Tomasic, Isaac Simmons, John Zimmerman
136
Voted
EMNLP
2010
15 years 1 months ago
Combining Unsupervised and Supervised Alignments for MT: An Empirical Study
Word alignment plays a central role in statistical MT (SMT) since almost all SMT systems extract translation rules from word aligned parallel training data. While most SMT systems...
Jinxi Xu, Antti-Veikko I. Rosti