Παρακαλώ χρησιμοποιήστε αυτό το αναγνωριστικό για να παραπέμψετε ή να δημιουργήσετε σύνδεσμο προς αυτό το τεκμήριο: https://hdl.handle.net/20.500.14279/12879
Πεδίο DCΤιμήΓλώσσα
dc.contributor.advisorDjouvas, Constantinos-
dc.contributor.authorStavrinos, Adamos-
dc.date.accessioned2018-11-05T07:04:22Z-
dc.date.available2018-11-05T07:04:22Z-
dc.date.issued2018-05-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/12879-
dc.description.abstractOn a daily basis, each one of us is required to decide on a number of issues. Difficulty varies depending by the importance and the options of the decision. As the time passes by, technological advances help millions of users in decision making by creating new methods and tools that users can easily use and utilize. The aim of this study was to create an online platform that assists users in the case of exodus decision. To do so, state of the art technologies will be used including M.E.A.N (MongoDB, ExpressJS, AngularJS, NodeJS) stack and machine learning. Furthermore, the methods used are explained in detail as well as the reason M.E.A.N stack was selected against other available technologies. At the end of this research, the platform implemented was evaluated, providing users with an order list of best matching options for exodus based on the answers a user provided in a preceding questionnaire. In addition, this study evaluates the performance of machine learning in the domain of exodus selection. The research concludes with some results regarding the successful fulfilment of all research question. Also, we will provide some results of how machine learning reacted with the results given.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.publisherDepartment of Communication and Internet Studies, Faculty of Communication and Media Studies, Cyprus University of Technologyen_US
dc.rightsΑπαγορεύεται η δημοσίευση ή αναπαραγωγή, ηλεκτρονική ή άλλη χωρίς τη γραπτή συγκατάθεση του δημιουργού και κάτοχου των πνευματικών δικαιωμάτων.en_US
dc.subjectMachine learningen_US
dc.subjectRecommender systemsen_US
dc.subjectWeb developingen_US
dc.subjectDecision makingen_US
dc.titleWeb-based decision making using machine learning and recommender system: the case of exodusen_US
dc.typeBachelors Thesisen_US
dc.affiliationCyprus University of Technologyen_US
dc.relation.deptDepartment of Communication and Internet Studiesen_US
dc.description.statusCompleteden_US
cut.common.academicyear2017-2018en_US
dc.relation.facultyFaculty of Communication and Media Studiesen_US
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_46ec-
item.cerifentitytypePublications-
item.openairetypebachelorThesis-
crisitem.author.deptDepartment of Communication and Internet Studies-
crisitem.author.facultyFaculty of Communication and Media Studies-
crisitem.author.orcid0000-0003-1215-7294-
crisitem.author.parentorgFaculty of Communication and Media Studies-
Εμφανίζεται στις συλλογές:Πτυχιακές Εργασίες/ Bachelor's Degree Theses
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