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» Training a Natural Language Generator From Unaligned Data
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JASIS
2000
143views more  JASIS 2000»
14 years 11 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
ACL
2007
15 years 23 days 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 4 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
WWW
2007
ACM
15 years 12 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
EMNLP
2010
14 years 9 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