Multi strategies-based resources recommendation in learning team

Lin Gong*, Zi Jian Zhang, Jian Xie

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Learning team has become an important foundation for collaborative work. In a team, according to the knowledge of members and task requirements, how to recommend learning resources to the appropriate team member is a key factor of success. This paper firstly reviewed related methods and concepts in knowledge management and recommendation. Then, it constructed different models for task, knowledge, team member and learning resource. The two strategies of resources recommendation were proposed. One was based on similarity measurement and another is based on knowledge background and experience of team members. Based on the two strategies, learning resources were recommended to team members. Finally, the prototype system was built for practical validation.

Original languageEnglish
Title of host publicationAdvanced Manufacturing and Industrial Engineering
PublisherTrans Tech Publications Ltd.
Pages1187-1193
Number of pages7
ISBN (Print)9783038352075
DOIs
Publication statusPublished - 2014
Event4th International Conference on Advanced Engineering Materials and Technology, AEMT 2014 - Xiamen, China
Duration: 14 Jun 201415 Jun 2014

Publication series

NameAdvanced Materials Research
Volume1006-1007
ISSN (Print)1022-6680
ISSN (Electronic)1662-8985

Conference

Conference4th International Conference on Advanced Engineering Materials and Technology, AEMT 2014
Country/TerritoryChina
CityXiamen
Period14/06/1415/06/14

Keywords

  • Knowledge modeling
  • Knowledge recommendation
  • Learning resources
  • Similarity measurement
  • Team collaboration

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