On the limited memory BFGS method for large scale optimization
Mathematical Programming: Series A and B
Natural language understanding (2nd ed.)
Natural language understanding (2nd ed.)
A maximum entropy approach to natural language processing
Computational Linguistics
Foundations of statistical natural language processing
Foundations of statistical natural language processing
A maximum-entropy-inspired parser
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Integrating top-down and bottom-up approaches in inductive logic programming: applications in natural language processing and relational data mining
Learning to transform natural to formal languages
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
Learning to parse database queries using inductive logic programming
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
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We formulate the problem of transformation natural language sentences as the determination of sequence of actions that transforms an input sentence to its logical form. The model to determine a sequence of actions for a corresponding sentence is automatically estimated from a corpus of sentences and their logical forms with a MEM framework. Experimental results show that the MEM framework are suitable for the transformation problem and archived a comparable result in comparison with other methods.