Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/515466
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dc.coverage.spatial
dc.date.accessioned2023-10-03T09:02:48Z-
dc.date.available2023-10-03T09:02:48Z-
dc.identifier.urihttp://hdl.handle.net/10603/515466-
dc.description.abstractnewline
dc.format.extent190p.
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titlePredict and analyse the movie data using multimodal and hybrid deep learning
dc.title.alternative
dc.creator.researcherSahu, Sandipan
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Artificial Intelligence
dc.subject.keywordEngineering and Technology
dc.description.noteThe thesis includes various proposed methodologies, algorithms to predict the outcome of movie at early stage of movie production and assess the acceptance of a forthcoming film among various age demographics. In this thesis we also Recommendation System for Upcoming Movies and Impact of social media on predicting movie box-office revenue.
dc.contributor.guideKumar, Raghvendra and Shafi, Pathan Mohd.
dc.publisher.placeGunupur
dc.publisher.universityGIET University, Gunupur
dc.publisher.institutionComputer Science and Engineering
dc.date.registered
dc.date.completed2023
dc.date.awarded2023
dc.format.dimensions
dc.format.accompanyingmaterialDVD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Computer Science and Engineering

Files in This Item:
File Description SizeFormat 
01_title.pdfAttached File93.52 kBAdobe PDFView/Open
02_prelim pages.pdf414.1 kBAdobe PDFView/Open
03_table of contents.pdf88.51 kBAdobe PDFView/Open
04_abstract.pdf52.95 kBAdobe PDFView/Open
05_chapter 1.pdf905.01 kBAdobe PDFView/Open
06_chapter 2.pdf184.19 kBAdobe PDFView/Open
07_chapter 3.pdf2.08 MBAdobe PDFView/Open
08_chapter 4.pdf1.16 MBAdobe PDFView/Open
09_chapter 5.pdf1.56 MBAdobe PDFView/Open
10_chapter 6.pdf57.83 kBAdobe PDFView/Open
11_annexure.pdf341.81 kBAdobe PDFView/Open
80_recommendation.pdf57.83 kBAdobe PDFView/Open


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