Proceedings of the 2015 3rd International Conference on Management Science, Education Technology, Arts, Social Science and Economics

Constructing knowledge map for MOOC using data mining methods

Authors
Junmeng Hou, Ruifang Liu, Yu Zhang
Corresponding Author
Junmeng Hou
Available Online November 2015.
DOI
10.2991/msetasse-15.2015.204How to use a DOI?
Keywords
MOOC; data mining; k-means clustering; knowledge map
Abstract

Although Massive Open Online Courses(MOOCs) have become a way of online study used by millions of peopleacross the world, so many websites and courses often confuse people that they can’t choose the courses they need quickly and accurately. In this paper, we present an approach that constructknowledge map for courses using data mining methods. The data mining algorithm combines all the courses of several MOOC websites, and takes the text descriptions of the courses given in the website into account. People can choose corresponding knowledge map for a series of courses according to their needs.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2015 3rd International Conference on Management Science, Education Technology, Arts, Social Science and Economics
Series
Advances in Social Science, Education and Humanities Research
Publication Date
November 2015
ISBN
10.2991/msetasse-15.2015.204
ISSN
2352-5398
DOI
10.2991/msetasse-15.2015.204How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Junmeng Hou
AU  - Ruifang Liu
AU  - Yu Zhang
PY  - 2015/11
DA  - 2015/11
TI  - Constructing knowledge map for MOOC using data mining methods
BT  - Proceedings of the 2015 3rd International Conference on Management Science, Education Technology, Arts, Social Science and Economics
PB  - Atlantis Press
SP  - 938
EP  - 943
SN  - 2352-5398
UR  - https://doi.org/10.2991/msetasse-15.2015.204
DO  - 10.2991/msetasse-15.2015.204
ID  - Hou2015/11
ER  -