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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Veröffentlicht in:	International journal of advanced computer science & applications Jg. 11; H. 7
1. Verfasser:	Rivera, Jerson Erick Herrera
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	West Yorkshire Science and Information (SAI) Organization Limited 2020
Schlagworte:	Algorithms Colleges & universities Engineering education Hybrid systems Machine learning Natural language processing Recommender systems Students
ISSN:	2158-107X, 2156-5570
Online-Zugang:	Volltext
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