Grammar Inference Automata Induction and Language Acquisition

نویسندگان

  • Rajesh Parekh
  • Vasant Honavar
چکیده

The natural language learning problem has attracted the attention of researchers for several decades Computational and formal models of language acquisition have provided some preliminary yet promising insights of how children learn the lan guage of their community Further these formal models also provide an operational framework for the numerous practical applications of language learning We will survey some of the key results in formal language learning In particular we will discuss the prominent computational approaches for learning di erent classes of for mal languages and discuss how these t in the broad context of natural language learning

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منابع مشابه

Grammar Inference , Automata Induction , and Language

The natural language learning problem has attracted the attention of researchers for several decades. Computational and formal models of language acquisition have provided some preliminary, yet promising insights of how children learn the language of their community. Further, these formal models also provide an operational framework for the numerous practical applications of language learning. ...

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Appears in 1997 Workshop on Automata Induction , Grammatical Inference , and Language Acquisition

For most natural language processing tasks, a parser that maps sentences into a semantic representation is signiicantly more useful than a grammar or au-tomata that simply recognizes syntactically well-formed strings. This paper reviews our work on using inductive logic programming methods to learn de-terministic shift-reduce parsers that translate natural language into a semantic representatio...

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To appear in 1997 Workshop on Automata Induction , Grammatical Inference , and Language Acquisition

For most natural language processing tasks, a parser that maps sentences into a semantic representation is signiicantly more useful than a grammar or au-tomata that simply recognizes syntactically well-formed strings. This paper reviews our work on using inductive logic programming methods to learn de-terministic shift-reduce parsers that translate natural language into a semantic representatio...

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Learning Finite State Machines

The terms grammatical inference and grammar induction both seem to indicate that techniques aiming at building grammatical formalisms when given some information about a language are not concerned with automata or other finite state machines. This is far from true, and many of the more important results in grammatical inference rely heavily on automata formalisms, and particularly on determinis...

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Appears in Proceedings of the ICML - 97 Workshop on Automata Induction , Grammatical Inference , and Language Aquicision

For most natural language processing tasks, a parser that maps sentences into a semantic representation is signi cantly more useful than a grammar or automata that simply recognizes syntactically wellformed strings. This paper reviews our work on using inductive logic programming methods to learn deterministic shift-reduce parsers that translate natural language into a semantic representation. ...

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تاریخ انتشار 1998