Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/453273
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dc.coverage.spatialData mining approach for recommending seats to students based on medical image analysis
dc.date.accessioned2023-01-27T04:29:48Z-
dc.date.available2023-01-27T04:29:48Z-
dc.identifier.urihttp://hdl.handle.net/10603/453273-
dc.description.abstractEducation field plays an important role in the upcoming research newlineand is used in the enhancement of students knowledge and detecting their newlinelearning capability. Data Mining and Image Processing is a major research newlinefield which aims at devising algorithms to improve educational results and newlineexplain educational strategies for further decision making. newlineImproving of students learning capability is very important in newlineeducation system. Learning capability will be varied to different types of newlinestudents for example learning capability will high to excellent students and newlinelearning capability will be low to average students. The main aim of the newlineresearch work is to improve the average students learning capability based on newlinerecommending of correct seat in class room that means based on seat newlinerecommendation system. newlineSeat Recommendation System is very important to average students newlinebecause of their problems such as lack of concentration, unnecessarily talk newlinewith their friends, low level listening capability and low observing ability newlinewhen they are seated in last row in class room with eye defects. To overcome newlinethe above average students learning problems, the research work introduce the newlinenovel models for seat recommendation system in an effective and easy newlinemanner. newline
dc.format.extentxv,114p.
dc.languageEnglish
dc.relationp.101-113
dc.rightsuniversity
dc.titleData mining approach for recommending seats to students based on medical image analysis
dc.title.alternative
dc.creator.researcherJothi Kalpana J K
dc.subject.keywordInformation Retrieval
dc.subject.keywordPattern Matching
dc.subject.keywordFuzzy Logic
dc.description.note
dc.contributor.guideVenkatalakshmi K
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registered
dc.date.completed2019
dc.date.awarded2019
dc.format.dimensions21cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Information and Communication Engineering

Files in This Item:
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01_title.pdfAttached File22.62 kBAdobe PDFView/Open
02_prelim pages.pdf1.57 MBAdobe PDFView/Open
03_content.pdf278.12 kBAdobe PDFView/Open
04_abstract.pdf114.49 kBAdobe PDFView/Open
05_chapter 1.pdf373.36 kBAdobe PDFView/Open
06_chapter 2.pdf326.66 kBAdobe PDFView/Open
07_chapter 3.pdf401.22 kBAdobe PDFView/Open
08_chapter 4.pdf617.02 kBAdobe PDFView/Open
09_chapter 5.pdf924.88 kBAdobe PDFView/Open
10_chapter 6.pdf858.42 kBAdobe PDFView/Open
11_chapter 7.pdf249.97 kBAdobe PDFView/Open
12_annexures.pdf192.72 kBAdobe PDFView/Open
80_recommendation.pdf156.74 kBAdobe PDFView/Open


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