Under-graduate study recommendations using association rule mining

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dc.contributor.authorAsim, Hira
dc.date.accessioned2018-06-12T07:46:52Z
dc.date.available2018-06-12T07:46:52Z
dc.date.issued2018
dc.descriptionSupervised by: Dr. Malik Tahir Hassanen_US
dc.description.abstractIn this research work, we are aimed to provide recommendations regarding degree programs and institutes at under-graduate level to students who have successfully passed their intermediate. In order to recommend we collected data via Google survey form regarding background study area, future goals and interests of individuals who are successfully done with their under-graduate studies for least. After the data has been collected it was being pre-proceed, visualized and analyzed for future use. Data mining technique named Association Rule Mining is applied on the data to find hidden patterns and trends in it. The results of the Association Rule Mining technique are the recommendations to the students regarding suitable under-graduate degree programs and educational institutes as per their background study stream, area of interest and future goals. Recommendations are based on the information collected where students and graduates have alike choices regarding study streams, area of interest and future goals. We are hopeful that this contribution will be a huge step forward towards the betterment of educational environment as well as a source of proper guidance for the students who are done with their intermediate and now aimed to take admission in an under-graduate program in a well reputed university in Pakistanen_US
dc.identifier.urihttps://escholar.umt.edu.pk/handle/123456789/3006
dc.language.isoenen_US
dc.publisherUniversity of Management and Technologen_US
dc.subjectData mining techniqueen_US
dc.subjectAssociation Rule Miningen_US
dc.subjectM.Philen_US
dc.titleUnder-graduate study recommendations using association rule miningen_US
dc.typeThesisen_US
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