MERAL Myanmar Education Research and Learning Portal
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String Similarity Measures for Myanmar Language (Burmese)
http://hdl.handle.net/20.500.12678/0000007687
http://hdl.handle.net/20.500.12678/00000076871f7b2119-902c-4e30-8255-1906b68489f1
fa3ccd4e-b876-4c06-9e77-aedda03505a9
Name / File | License | Actions |
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String Similarity Measures for Myanmar Language (Burmese).pdf (263 KB)
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Publication type | ||||||
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Journal article | ||||||
Upload type | ||||||
Publication | ||||||
Title | ||||||
Title | String Similarity Measures for Myanmar Language (Burmese) | |||||
Language | en | |||||
Publication date | 2019-09-17 | |||||
Authors | ||||||
Khaing Hsu Wai | ||||||
Ye Kyaw Thu | ||||||
Hnin Aye Thant | ||||||
Swe Zin Moe | ||||||
Thepchai Supnithi | ||||||
Description | ||||||
Measuring string similarity is useful for a broad range of applications. It plays an important role in machine learning, information retrieval, natural language processing, error encoding, and bioinformatics. Measuring string similarity is a fundamental operation of data science, important for data cleaning and integration. Real-world applications such as spell checking, duplicate finding, searching similar words, and retrieving tasks use string similarity. In this study, string similarity metrics have been calculated for Burmese (Myanmar language). The encoding table for Burmese has been built based on the pronunciation similarity of characters and vowel combination positions with a consonant. According to the table, strings and words are encoded. Similarity distance is measured between the dataset and query words. Previous string similarity approaches are not suitable for fuzzy string matching of tonal-based Burmese. Therefore, three mapping approaches are proposed in this study. |
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Keywords | ||||||
Myanmar character, Burmese, String similarity metrics, Phonetic similarity, Fuzzy string matching | ||||||
Journal articles | ||||||
https://www.aclweb.org/anthology/2019.nsurl-1.14.pdf | ||||||
String Similarity Measures for Myanmar Language (Burmese) | ||||||
Pages 94-102 | ||||||
https://www.aclweb.org/anthology/2019.nsurl-1.14 |