Word segmentation using domain knowledge based on conditional random fields

被引：1

作者：

Fukuda, Takuya ^{[1
]}

Izzumi, Masataka ^{[1
]}

Miura, Takao ^{[1
]}

机构：

[1] Hosei Univ, Dept Elect & Elect Engn, Tokyo, Japan

来源：

19TH IEEE INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE, VOL II, PROCEEDINGS | 2007年

关键词：

D O I：

10.1109/ICTAI.2007.93

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this investigation, we propose an experimental approach for word segmentation in Japanese under domain-dependent situation. We apply Conditional Random Fields (CRF) to our issue. CRF learns several probabilistic parameters from training data with specific feature functions dependent on domains. Here we propose how to define domain specific feature functions.

引用

页码：436 / 439

页数：4

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