Approximate string matching techniques for effective CLIR among Indian languages

被引：0

作者：

Makin, Ranbeer ^{[1
]}

Pandey, Nikita ^{[1
]}

Pingali, Prasad ^{[1
]}

Varma, Vasudeva ^{[1
]}

机构：

[1] Int Inst Informat Technol, Hyderabad, Andhra Pradesh, India

来源：

APPLICATIONS OF FUZZY SETS THEORY | 2007年 / 4578卷

关键词：

telugu-hindi CLIR; Indian languages; cognate; identification;

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：

Commonly used vocabulary in Indian language documents found on the web contain a number of words that have Sanskrit, Persian or English origin. However, such words may be written in different scripts with slight variations in spelling and morphology. In this paper we explore approximate string matching techniques to exploit this situation of relatively large number of cognates among Indian languages, which are higher when compared to an Indian language and a non-Indian language. We present an approach to identify cognates and make use of them for improving dictionary based CLIR when the query and documents both belong to two different Indian languages. We conduct experiments using a Hindi document collection and a set of Telugu queries and report the improvement due to cognate recognition and translation.

引用

页码：430 / +

页数：2

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