The acquisition of syntactic knowledge
The acquisition of syntactic knowledge
Mechanisms of sentence processing: assigning roles to constituents
Parallel distributed processing
Automatic acquisition of subcategorization frames from tagged text
HLT '91 Proceedings of the workshop on Speech and Natural Language
The acquisition and use of context-dependent grammars for English
Computational Linguistics
Efficient Parsing for Natural Language: A Fast Algorithm for Practical Systems
Efficient Parsing for Natural Language: A Fast Algorithm for Practical Systems
The Architecture of Cognition
Learning Logical Definitions from Relations
Machine Learning
A Computerized Prototype Natural Language Tour Guide
A Computerized Prototype Natural Language Tour Guide
University of Massachusetts: MUC-4 test results and analysis
MUC4 '92 Proceedings of the 4th conference on Message understanding
Ontology learning from text: A look back and into the future
ACM Computing Surveys (CSUR)
Generating OLAP queries from natural language specification
Proceedings of the International Conference on Advances in Computing, Communications and Informatics
Interacting with data warehouse by using a natural language interface
NLDB'12 Proceedings of the 17th international conference on Applications of Natural Language Processing and Information Systems
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Automating the construction of semantic grammars is a difficult and interesting problem for machine learning. This paper shows how the semantic-grammar acquisition problem can be viewed as the learning of search-control heuristics in a logic program. Appropriate control rules are learned using a new first-order induction algorithm that automatically invents useful syntactic and semantic categories. Empirical results show that the learned parsers generalize well to novel sentences and out-perform previous approaches based on connectionist techniques.