Survey: Finite-state technology in natural language processing

被引:5
|
作者
Maletti, Andreas [1 ]
机构
[1] Univ Stuttgart, Inst Nat Language Proc, Pfaffenwaldring 5b, D-70569 Stuttgart, Germany
关键词
Finite-state automaton; Tree automaton; Context-free grammar; Natural language processing; Tokenization; Part-of-speech tagging; Parsing; Machine translation; MAXIMUM-LIKELIHOOD; PROBABILISTIC FUNCTIONS;
D O I
10.1016/j.tcs.2016.05.030
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In this survey, we will discuss current uses of finite-state information in several statistical natural language processing tasks. To this end, we will review standard approaches in tokenization, part-of-speech tagging, and parsing, and illustrate the utility of finite-state information and technology in these areas. The particular problems were chosen to allow a natural progression from simple prediction to structured prediction. We aim for a sufficiently formal presentation suitable for readers with a background in automata theory that allows to appreciate the contribution of finite-state approaches, but we will not discuss practical issues outside the core ideas. We provide instructive examples and pointers into the relevant literature for all constructions. We close with an outlook on finite-state technology in statistical machine translation. (C) 2016 Elsevier B.V. All rights reserved.
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页码:2 / 17
页数:16
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