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The Pennsylvania State University CiteSeerX Archives (36)
Naushad Uzzaman (5)
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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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