Learning deterministic regular grammars from stochastic samples in polynomial time

被引：71

作者：

Carrasco, RC ^{[1
]}

Oncina, J ^{[1
]}

机构：

[1] Univ Alicante, Dept Lenguajes & Sistemas Informat, Alicante 03071, Spain

来源：

RAIRO-INFORMATIQUE THEORIQUE ET APPLICATIONS-THEORETICAL INFORMATICS AND APPLICATIONS | 1999年 / 33卷 / 01期

关键词：

D O I：

10.1051/ita:1999102

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, the identification of stochastic regular languages is addressed. For this purpose, we propose a class of algorithms which allow for the identification of the structure of the minimal stochastic automaton generating the language. It is shown that the time needed grows only linearly with the size of the sample set and a measure of the complexity of the task is provided. Experimentally, our implementation proves very fast for application purposes.

引用

页码：1 / 19

页数：19

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