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ReserarchID
027C9
In this paper, we have developed a mono-linguistic Bengali news corpus using knowledge based AI (Artificial Intelligence) technique from some widely read Bengali newspapers which will be used as a reference corpus and will be very useful for lexicon development, morphological analysis, and automatic parts of speech detection. The corpus contains 74,698 word forms. The words in the lexicon are annotated with a combination of manual tags addressing Parts-of-Speech, Stemming, Morphemes, and other grammatical features are very important for almost all Natural Language Processing (NLP) applications. The lexicon contains around 14 thousand entries.
Abdul Matin. 2017. \u201cAnnotated Bangla News Corpus and Lexicon Development with POS Tagging and Stemming\u201d. Global Journal of Research in Engineering - J: General Engineering GJRE-J Volume 17 (GJRE Volume 17 Issue J1): .
Crossref Journal DOI 10.17406/gjre
Print ISSN 0975-5861
e-ISSN 2249-4596
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Total Score: 105
Country: Bangladesh
Subject: Global Journal of Research in Engineering - J: General Engineering
Authors: Tasnim Haider Chaudhury, Abdul Matin, M.S. Hossain, Asie Uzzaman, Md. Masum (PhD/Dr. count: 0)
View Count (all-time): 220
Total Views (Real + Logic): 3576
Total Downloads (simulated): 1687
Publish Date: 2017 05, Thu
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In this paper, we have developed a mono-linguistic Bengali news corpus using knowledge based AI (Artificial Intelligence) technique from some widely read Bengali newspapers which will be used as a reference corpus and will be very useful for lexicon development, morphological analysis, and automatic parts of speech detection. The corpus contains 74,698 word forms. The words in the lexicon are annotated with a combination of manual tags addressing Parts-of-Speech, Stemming, Morphemes, and other grammatical features are very important for almost all Natural Language Processing (NLP) applications. The lexicon contains around 14 thousand entries.
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