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Copying Case Detection with Data Mining

dc.contributor.authorTarhan, Halil Hakan
dc.contributor.authorAydin, Nizamettin
dc.date.accessioned2026-06-27T14:10:09Z
dc.date.issued2017
dc.description.abstractCentral examinations arc one of the measurement and evaluation tools used throughout the world to select from among the participants, to rank, to reduce the number of candidates before the interview or determine whether the level of education varies between regional and demographic criteria. A more objective measurement and evaluation can be made through the questioning of multiple choice questions compared to open ended questions. In this study, we present a data mining model proposed for the detection of copying cases at central examinations and a case analysis using this model.en
dc.identifier.endpage434
dc.identifier.isbn978-1-5386-0930-9
dc.identifier.startpage430
dc.identifier.urihttps://hdl.handle.net/20.500.14981/57485
dc.identifier.wos000426856900080
dc.language.isotur
dc.publisherIEEE
dc.relation.conference2017 International Conference on Computer Science and Engineering (UBMK)
dc.relation.ispartof2017 INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND ENGINEERING (UBMK)
dc.subjectcopying case or cheating detection on central examinations
dc.subjectdata mining
dc.subjectclustering
dc.subjectComputer Science
dc.titleCopying Case Detection with Data Mining
dc.typeProceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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