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Title: Pattern based bootstrapping approaches For natural language processing of Morphologically rich languages
Researcher: Balaji J
Guide(s): Geetha T V
Keywords: Natural Language Processing
Upload Date: 17-Feb-2015
University: Anna University
Completed Date: 01/10/2014
Abstract: This thesis attempts to tackle Natural Language Processing NLP tasks by exploiting the special characteristics of morphologically rich newlineLanguages In this thesis we use Tamil as an example to show how newlinecomputational approaches to such morphologically rich languages need to be newlinedifferent Our initial work used the special characteristics to build rule based newlinesystems However as is the case with most rule based systems only the newlinenatural language sentences of a specific domain could be tackled As a result newlineof our experience in building the rule based systems we were able to identify newlinethe linguistic features that could be effectively used for the NLP processing of newlinemorphologically rich languages newlineIn order to overcome the limitations of rule based approaches we newlinenext attempted to explore machine learning approaches One of the common newlinemachine learning approaches used for languages such as English, is newlinesupervised learning Supervised approaches require a large labor intensive newlineannotated and labeled corpus which is not available for resource scarce newlinelanguages such as Tamil Unsupervised approaches on the other hand take a newlinelong time to converge to a solution We first attempted an unsupervised approach newlinefor the semantic relation extraction From our experience with the unsupervised newlineapproach we found that the partially free word order characteristic of a newlinemorphologically rich language did not lend itself to fast convergence to a newlinesolution In this context we decided that semi supervised approaches that require a limited number of trained samples could be attempted newline newline
Pagination: xxv, 304p.
Appears in Departments:Faculty of Information and Communication Engineering

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02_certificate.pdf1.28 MBAdobe PDFView/Open
03_abstract.pdf33.99 kBAdobe PDFView/Open
04_acknowledgement.pdf21.53 kBAdobe PDFView/Open
05_content.pdf67.8 kBAdobe PDFView/Open
06_chapter1.pdf143.67 kBAdobe PDFView/Open
07_chapter2.pdf259.05 kBAdobe PDFView/Open
08_chapter3.pdf877.54 kBAdobe PDFView/Open
09_chapter4.pdf1.03 MBAdobe PDFView/Open
10_chapter5.pdf694.99 kBAdobe PDFView/Open
11_chapter6.pdf1.5 MBAdobe PDFView/Open
12_chapter7.pdf1.83 MBAdobe PDFView/Open
13_chapter8.pdf24.56 kBAdobe PDFView/Open
14_reference.pdf94.41 kBAdobe PDFView/Open
15_publication.pdf37.24 kBAdobe PDFView/Open

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