Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/355028
Title: Development of Regression and Population Models Based on Zipfs Law and its Application to Authorship Attribution
Researcher: Lakshmisridevi, S
Guide(s): Devanathan, R
Keywords: Computer Science
Computer Science Artificial Intelligence
Engineering and Technology
University: Hindustan University
Completed Date: 2018
Abstract: Quantitative linguistics is a relatively new area where analytical newlinetechniques and computer-based modelling are applied to linguistics texts. The newlineage-old questions, such as, Who wrote Shakespeare? , take an analytical newlinemeaning in this context. Quantitative linguistics aims to model language texts newlineincluding English language. Such models have several applications, text newlineclassification, authorship attribution, natural language identification, language newlinelearning, text forensics, medical diagnostics etc. An explosive growth in terms newlineof results appearing in various conferences ranging from language and newlineliterature through machine learning and computation to law and forensics has newlinetaken place.
Pagination: 
URI: http://hdl.handle.net/10603/355028
Appears in Departments:Department of Computer Application

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10_chapter 1.pdfAttached File131.62 kBAdobe PDFView/Open
11_chapter 2.pdf206.77 kBAdobe PDFView/Open
12_chapter 3.pdf2.01 MBAdobe PDFView/Open
13_chapter 4.pdf198.43 kBAdobe PDFView/Open
14_chapter 5.pdf260.78 kBAdobe PDFView/Open
15_chapter 6.pdf361.99 kBAdobe PDFView/Open
16_chapter 7.pdf230.7 kBAdobe PDFView/Open
19_references.pdf245.45 kBAdobe PDFView/Open
1_title.pdf83.29 kBAdobe PDFView/Open
2_certificate.pdf405.45 kBAdobe PDFView/Open
3_declaration.pdf165.2 kBAdobe PDFView/Open
4_abstract.pdf175.89 kBAdobe PDFView/Open
6_contents.pdf89.3 kBAdobe PDFView/Open
7_tables.pdf163.94 kBAdobe PDFView/Open
80_recommendation.pdf312.61 kBAdobe PDFView/Open
8_figures.pdf2.73 MBAdobe PDFView/Open
9_symbols.pdf180.91 kBAdobe PDFView/Open
conclusion.pdf141.4 kBAdobe PDFView/Open
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