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Hits 1 – 20 of 36

1	Bidirectional Bengali Script and Meetei Mayek Transliteration of Web Based Manipuri News Corpus
	Thoudam Doren Singh
	In: http://www.aclweb.org/anthology/W/W12/W12-5016.pdf (2012)
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2	How Difficult is it to Develop a Perfect Spell-checker? A Cross-linguistic Analysis through Complex Network Approach
	Monojit Choudhury; Markose Thomas; Animesh Mukherjee...
	In: http://arxiv.org/pdf/physics/0703198v1.pdf (2007)
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3	Unsupervised morphological parsing of Bengali. Language Resources and Evaluation
	Sajib Dasgupta; Vincent Ng
	In: http://www.hlt.utdallas.edu/~sajib/LRE.fdf (2006)
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4	A Comprehensive Bangla Spelling Checker
	Naushad Uzzaman; Mumit Khan
	In: http://www.naushadzaman.com/ComprehensiveSpeller.pdf (2006)
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5	A Double Metaphone Encoding for Bangla and its Application in Spelling Checker
	Naushad Uzzaman
	In: http://www.bracu.ac.bd/research/crblp/papers/DoubleMetaphoneSpell.pdf (2005)
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6	An MLP using Hough transform based fuzzy feature extraction for Bengali script recognition
	Shamik Sural; P.K. Das
	In: http://www.facweb.iitkgp.ernet.in/~shamik/papers/1999_PRL.pdf (1999)
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7	A global perspective on bilingualism and bilingual education. ERIC Digest. (ERIC Document Reproduction Service No. ED435168
	G. Richard Tucker; Carnegie Mellon University
	In: http://www.cal.org/resources/digest/digest_pdfs/9904-tucker-globalBE.pdf (1999)
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8	Bengali and Hindi to English Cross-language Text Retrieval under Limited Resources
	Debasis M; Ipan D; Mayank Gupta...
	In: http://www.clef-campaign.org/2007/working_notes/mandalCLEF2007.pdf
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9	A Faster Approach to Sort Unicode Represented Bengali Words
	Aamira Shabnam; Tapashee Tabassum
	In: http://www.ijcaonline.org/research/volume126/number11/shabnam-2015-ijca-906224.pdf
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10	THE DISTRIBUTION AND REALIZATION OF H TONES IN BENGALI
	Sameer Ud Dowla Khan
	In: http://www.linguistics.ucla.edu/faciliti/workpapph/106/The distribution and realization of H tones in Bengali.pdf
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11	Combining Bilingual and Comparable Corpora for Low Resource Machine Translation
	Ann Irvine; Chris Callison-burch
	In: http://wing.comp.nus.edu.sg/~antho/W/W13/W13-2233.pdf
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12	Combining Bilingual and Comparable Corpora for Low Resource Machine Translation
	Ann Irvine; Chris Callison-burch
	In: http://www.cs.jhu.edu/~ccb/publications/combining-bilingual-and-comparable-corpora.pdf
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13	Bengali Question Classification: Towards Developing QA System ABSTRACT
	Somnath Banerjee; Sivaji Bandyopadhyay
	In: http://www.aclweb.org/anthology/W/W12/W12-5003.pdf
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14	SentiWordNet for Indian Languages
	Amitava Das; Sivaji B
	In: http://aclweb.org/anthology-new/W/W10/W10-3208.pdf
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15	Combining Bilingual and Comparable Corpora for Low Resource Machine Translation
	Ann Irvine; Chris Callison-burch
	In: http://www.cs.jhu.edu/~anni/papers/irvineCCB_WMT13.pdf
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16	History (forward n-gram) or Future (backward n-gram)? Which model to consider for n-gram analysis in Bangla?
	Naira Khan; Md. Tarek Habib; Md. Jahangir Alam...
	In: http://www.naushadzaman.com/iccit06_backwardn-gram.pdf
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17	GOBINDA KOLE
	Pabitra Mitra
	In: http://www.facweb.iitkgp.ernet.in/~pabitra/paper/stemmer.pdf
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18	Analysis of Bangla Root Word for Universal Networking Language (UNL)
	Aloke Kumar Saha; M. F Mridha; Jugal Krishna Das
	In: http://research.ijcaonline.org/volume89/number17/pxc3894576.pdf
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19	Overview of Stemming Algorithms for Indian and Non-Indian Languages
	Dalwadi Bijal; Suthar Sanket
	In: http://ijcsit.com/docs/Volume+5/vol5issue02/ijcsit2014050241.pdf
	Abstract: Abstract — Stemming is a pre-processing step in Text Mining applications as well as a very common requirement of Natural Language processing functions. Stemming is the process for reducing inflected words to their stem. The main purpose of stemming is to reduce different grammatical forms / word forms of a word like its noun, adjective, verb, adverb etc. to its root form. Stemming is widely uses in Information Retrieval system and reduces the size of index files. We can say that the goal of stemming is to reduce inflectional forms and sometimes derivationally related forms of a word to a common base form. In this paper we have discussed different stemming algorithm for non-Indian and Indian language, methods of stemming, accuracy and errors.
	Keyword: Bengali; Estonian; Finno-Ugric languages (Finnish; Gujarati) are inflected. In such languages several words sharing the same; Hungarian; Indo-Aryan languages (Hindi; Malayalam and Kannada; Marathi; Telugu; Turkish
	URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.657.6091 http://ijcsit.com/docs/Volume+5/vol5issue02/ijcsit2014050241.pdf
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20	The akshara languages:
	In: http://www.york.ac.uk/media/psychology/crl/documents/sonalipapers/the akshara languages (Chapter 16 proofs).pdf
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