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A Student Course Recommender
2002 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

At Lulea University of Technology, the students are required to choose the courses they are interested in reading for the subsequent semester. It is the student's responsibility to make sure that (s)he gets the courses needed to graduate. If the choice is not made, even for mandatory courses, the student will not be allowed to take that course. It is also the student's responsibility to make sure that (s)he has read the prerequisite courses for their choices, as well as to make sure that the selected courses are all allowed to simultaneously be part of a degree. This thesis aims are to investigate how machine learning methods can be utilized to create a system that can recommend courses to students with a high degree of reliability and that learns from student course choices made. The goal is to create a system that can be easily extended with new functionality. The result of this work is a design and a prototype of a client/server architecture, which implements a course suggestion strategy using Bayesian Network modelling.

Place, publisher, year, edition, pages
2002.
Keyword [en]
Technology, Bayesian Networks, User Interest Modeling, Machine Learning
Keyword [sv]
Teknik
Identifiers
URN: urn:nbn:se:ltu:diva-43170ISRN: LTU-EX--02/279--SELocal ID: 11099db7-e77b-4dfb-b256-0ef093b9a643OAI: oai:DiVA.org:ltu-43170DiVA: diva2:1016399
Subject / course
Student thesis, at least 30 credits
Educational program
Computer Science and Engineering, master's level
Examiners
Note
Validerat; 20101217 (root)Available from: 2016-10-04 Created: 2016-10-04Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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  • de-DE
  • en-GB
  • en-US
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Output format
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