Organizing online computation for adaptive micro open education resource recommendation

Sun, G; Cui, T; Beydoun, G; Chen, S; Xu, D; Shen, J

Organizing online computation for adaptive micro open education resource recommendation

Sun, G Cui, T Beydoun, G

Chen, S Xu, D Shen, J

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, 10473 LNCS pp. 177 - 182
Issue Date:: 2017-01-01

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Field	Value	Language
dc.contributor.author	Sun, G	en_US
dc.contributor.author	Cui, T	en_US
dc.contributor.author	Beydoun, G https://orcid.org/0000-0001-8087-5445	en_US
dc.contributor.author	Chen, S	en_US
dc.contributor.author	Xu, D	en_US
dc.contributor.author	Shen, J https://orcid.org/0000-0002-9403-7140	en_US
dc.date.issued	2017-01-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, 10473 LNCS pp. 177 - 182	en_US
dc.identifier.isbn	9783319667324	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/127676
dc.description.abstract	© 2017, Springer International Publishing AG. Our previous work, Micro Learning as a Service (MLaaS), aimed to deliver adaptive micro open education resources (OERs). However, relying solely on the offline computation, the recommendation lacks rationality and timeliness. It is also difficult to make the first recommendation to a new learner. In this paper we introduce the organization of the online computation of the MLaaS. It targets at solving the cold start problem due to the shortage of learner information and real-time updates of the learner-micro OER profile.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.relation.isbasedon	10.1007/978-3-319-66733-1_19	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Organizing online computation for adaptive micro open education resource recommendation	en_US
dc.type	Conference Proceeding
utslib.citation.volume	10473 LNCS	en_US
utslib.for	0806 Information Systems	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
pubs.organisational-group	/University of Technology Sydney/Strength - CAMGIS - Centre for Advanced Modelling and Geospatial lnformation Systems
pubs.organisational-group	/University of Technology Sydney/Strength - PERSWADE - Centre on Persuasive Systems for Wise Adaptive Living
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	10473 LNCS	en_US

Abstract:

© 2017, Springer International Publishing AG. Our previous work, Micro Learning as a Service (MLaaS), aimed to deliver adaptive micro open education resources (OERs). However, relying solely on the offline computation, the recommendation lacks rationality and timeliness. It is also difficult to make the first recommendation to a new learner. In this paper we introduce the organization of the online computation of the MLaaS. It targets at solving the cold start problem due to the shortage of learner information and real-time updates of the learner-micro OER profile.

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http://hdl.handle.net/10453/127676