Wang, Guangyuan and Wang, Hua and Tao, Xiaohui and Zhang, Ji (2011) Positive influence dominating set in e-learning social networks. In: 10th International Conference on Web-Based Learning (ICWL 2011): Advances in Web-Based Learning, 8-10 Dec 2011, Hong Kong.
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Abstract
In recent years, the development of E-learning is rapid. Learning efficiency can be greatly improved if E-learning users' social networks properties can be effectively utilized. However, the nodes in most research models are the same type. The focus of our study is on E-learners' positive influence between their relationship. In this paper, we proposed a new model and selection algorithm named Weight Positive Influence Dominating Set (WPIDS) and analyzed its efficiency through a case study. By comparing the differences between WPIDS and that of Positive Influence Dominating Set (PIDS), we found that our model and algorithm are more effective than those of PIDS.
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| Item Type: | Conference or Workshop Item (Commonwealth Reporting Category E) (Paper) |
|---|---|
| Refereed: | Yes |
| Item Status: | Live Archive |
| Additional Information: | © 2011 Springer-Verlag. Permanent restricted access to published version due to publisher copyright policy. Series: Lecture Notes in Computer Science v.7048. |
| Depositing User: | Dr Xiaohui (Daniel) Tao |
| Faculty / Department / School: | Historic - Faculty of Sciences - Department of Maths and Computing |
| Date Deposited: | 20 Jun 2012 10:14 |
| Last Modified: | 13 Feb 2015 04:37 |
| Uncontrolled Keywords: | e-learning; weight positive dominating set; algorithm |
| Fields of Research : | 13 Education > 1303 Specialist Studies in Education > 130306 Educational Technology and Computing 08 Information and Computing Sciences > 0806 Information Systems > 080605 Decision Support and Group Support Systems 01 Mathematical Sciences > 0101 Pure Mathematics > 010107 Mathematical Logic, Set Theory, Lattices and Universal Algebra |
| Socio-Economic Objective: | E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences |
| Identification Number or DOI: | 10.1007/978-3-642-25813-8_9 |
| URI: | http://eprints.usq.edu.au/id/eprint/20181 |
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