A Hybrid Recommender System to Enrollment for Elective Subjects in Engineering Students using Classification Algorithms

One of the main problems that engineering university students face is making the correct decision regarding the lines of elective subjects to enroll based on available information (preferences, syllabus, schedules, subject content, possible academic performance, teacher, curriculum, and others). Und...

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Vydané v:	International journal of advanced computer science & applications Ročník 11; číslo 7
Hlavný autor:	Rivera, Jerson Erick Herrera
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	West Yorkshire Science and Information (SAI) Organization Limited 2020
Predmet:	Algorithms Colleges & universities Engineering education Hybrid systems Machine learning Natural language processing Recommender systems Students
ISSN:	2158-107X, 2156-5570
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