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ICTAI
2009
IEEE
14 years 3 months ago
Probabilistic Neural Logic Network Learning: Taking Cues from Neuro-Cognitive Processes
This paper describes an attempt to devise a knowledge discovery model that is inspired from the two theoretical frameworks of selectionism and constructivism in human cognitive le...
Henry Wai Kit Chia, Chew Lim Tan, Sam Yuan Sung
COLING
2010
13 years 3 months ago
Generative Alignment and Semantic Parsing for Learning from Ambiguous Supervision
We present a probabilistic generative model for learning semantic parsers from ambiguous supervision. Our approach learns from natural language sentences paired with world states ...
Joohyun Kim, Raymond J. Mooney
SARA
2005
Springer
14 years 2 months ago
Learning Regular Expressions from Noisy Sequences
Abstract. The presence of long gaps dramatically increases the difficulty of detecting and characterizing complex events hidden in long sequences. In order to cope with this proble...
Ugo Galassi, Attilio Giordana
JCST
2008
138views more  JCST 2008»
13 years 8 months ago
Predicting Chinese Abbreviations from Definitions: An Empirical Learning Approach Using Support Vector Regression
In Chinese, phrases and named entities play a central role in information retrieval. Abbreviations, however, make keyword-based approaches less effective. This paper presents an em...
Xu Sun, Houfeng Wang, Bo Wang 0003
LREC
2008
103views Education» more  LREC 2008»
13 years 10 months ago
Learning the Species of Biomedical Named Entities from Annotated Corpora
In biomedical articles, terms with the same surface forms are often used to refer to different entities across a number of model organisms, in which case determining the species b...
Xinglong Wang, Claire Grover