Data analysis for Understanding Healthcare Education Innovations

dc.contributor.advisorDr. Vania Demitrova
dc.contributor.authorFERIAL MOHAMMED S AL ALHARETH
dc.date2020
dc.date.accessioned2022-05-28T16:47:39Z
dc.date.available2022-05-28T16:47:39Z
dc.degree.departmentAdvanced Computer Science
dc.degree.grantorSchool of Computing/ University of Leeds
dc.description.abstractIn Natural Language Processing field, mining texts to extract valuable information from unstructured texts is a crucial task. Starting from pre-processing techniques until methods helping to obtain results such as information extraction or retrieval, categorization, clustering and summarization. The aim of this project is that using some of these techniques to identify some hidden topics and clusters to understand one very important segments of society, medical students. Therefore, a corpus of textual data collected by Health Education England was given to achieve this goal. Experiments were conducted and some results produced in terms of topics exploration and positive or negative clusters that could help to develop learning environment
dc.identifier.urihttps://drepo.sdl.edu.sa/handle/20.500.14154/36525
dc.language.isoen
dc.titleData analysis for Understanding Healthcare Education Innovations
sdl.thesis.levelMaster
sdl.thesis.sourceSACM - United Kingdom

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