A Hybrid Approach For Word Segmentation

被引：0

作者：

Mohammed, Ammar ^{[1
,2
]}

Karam, Mohamed ^{[3
]}

Hefny, Hesham ^{[3
]}

机构：

[1] Arab East Coll, Dept Comp Sci, Riyadh, Saudi Arabia

[2] Cairo Univ, Dept Comp Sci, ISSR, Giza, Egypt

[3] Cairo Univ, Inst Stat Studies & Res, Dept Comp Sci, Giza, Egypt

来源：

2015 SAI INTELLIGENT SYSTEMS CONFERENCE (INTELLISYS) | 2015年

关键词：

Word segmentation; Word statistics; Maximum matching; Hybrid methods; RECOGNITION;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Automatic word segmentation is the process of finding the most likely sequence of words from a sequence of characters without spaces. The central issues of the word segmentation process are the complexity and accuracy. This paper proposes a hybrid method for automatic word segmentation depending on a dictionary based approach, word-statistics and the length of the word. In comparison to the word segmentation using Maximum Length Descending Frequency and Entropy Rate method, the paper shows that the proposed method gives a better accuracy.

引用

页码：232 / 238

页数：7

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