Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/487832
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dc.coverage.spatial
dc.date.accessioned2023-05-31T12:07:26Z-
dc.date.available2023-05-31T12:07:26Z-
dc.identifier.urihttp://hdl.handle.net/10603/487832-
dc.description.abstractFile attached newline
dc.format.extentxiii, 231p
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titleInnovative cross domain adaptation approach for sentiment analysis
dc.title.alternative
dc.creator.researcherSave, Ashwini Manohar
dc.subject.keywordComputer Science
dc.subject.keywordCross domain sentiment analysis
dc.subject.keywordDeep learning
dc.subject.keywordEngineering and Technology
dc.subject.keywordMachine learning
dc.subject.keywordSentiment analysis
dc.description.noteLocation - Knowledge Resource Centre, Kalina
dc.contributor.guideShekokar, Narendra M
dc.publisher.placeMumbai
dc.publisher.universityUniversity of Mumbai
dc.publisher.institutionComputer Engineering, SVKM s Dwarkadas J. Sanghvi College of Engineering
dc.date.registered2017
dc.date.completed2021
dc.date.awarded2023
dc.format.dimensions30*21
dc.format.accompanyingmaterialCD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Computer Engineering, SVKM s Dwarkadas J. Sanghvi College of Engineering

Files in This Item:
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01_title.pdfAttached File93.38 kBAdobe PDFView/Open
02_prelim pages.pdf585.8 kBAdobe PDFView/Open
03_contents.pdf246.58 kBAdobe PDFView/Open
04_abstract.pdf86.05 kBAdobe PDFView/Open
05_chapter 1.pdf625.17 kBAdobe PDFView/Open
06_chapter 2.pdf481.99 kBAdobe PDFView/Open
07_chapter 3.pdf151.57 kBAdobe PDFView/Open
08_chapter 4.pdf326.49 kBAdobe PDFView/Open
09_chapter 5.pdf1.58 MBAdobe PDFView/Open
10_chapter 6.pdf1.7 MBAdobe PDFView/Open
11_chapter 7.pdf1.8 MBAdobe PDFView/Open
12_chapter 8.pdf485.06 kBAdobe PDFView/Open
13_chapter 9.pdf1.44 MBAdobe PDFView/Open
14_chapter 10.pdf233.23 kBAdobe PDFView/Open
15_annexures.pdf516.28 kBAdobe PDFView/Open
80_recommendation.pdf325.73 kBAdobe PDFView/Open


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