Abstract
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.
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Makin, R., Pandey, N., Pingali, P., Varma, V. (2007). Approximate String Matching Techniques for Effective CLIR Among Indian Languages. In: Masulli, F., Mitra, S., Pasi, G. (eds) Applications of Fuzzy Sets Theory. WILF 2007. Lecture Notes in Computer Science(), vol 4578. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73400-0_54
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DOI: https://doi.org/10.1007/978-3-540-73400-0_54
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73399-7
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