Positive influence dominating set in e-learning social networks

Wang, Guanyuan and Wang, Hua and Tao, Xiaohui and Zhang, Ji (2011) Positive influence dominating set in e-learning social networks. In: ICWL 2011: 10th International Conference on Web-Based Learning , 8-10 Dec 2011, Hong Kong.

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: Series: Lecture Notes in Computer Science, no. 7048. Permanent restricted access to published version due to publisher copyright policy.
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: 27 Sep 2013 00:56
Uncontrolled Keywords: e-learning; weight positive dominating set; algorithm
Fields of Research (FOR2008): 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 (SEO2008): E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI: doi: 10.1007/978-3-642-25813-8_9
URI: http://eprints.usq.edu.au/id/eprint/20181

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