Mining Learning Indicators Based on Academic Social Networking Repository: DBLP Case Study

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Social networking has been around for a while, but it has been generally been ignored for some time by academic investigators. Currently, this situation has been changed as academic usage and the importance of social software with the advancement of the Web 2.0 initiative. This article develops an integral approach that uses reasoning, mining and visualization techniques for identifying some of the academic indicators within the domain of a social network for scientific publications. The dataset used the DBLP XML Database that is dedicated for the domain of academic publications.

Keywords: Social Networking, Collaborative Learning, Web 2.0, DBLP
Stream: Technology in Learning; Maths, Science and Technology Learning
Presentation Type: Paper Presentation in English
Paper: A paper has not yet been submitted.

Prof. Jinan Fiaidhi

Professor, Department of Computer Science, Lakehead University
Thunder Bay, Ontario P7B 5E1, Canada

PgD (Essex University, 1983), PhD (Brunel University, 1986), Full Professor of Computer Science at Lakehead University, More than 100 refereed publications
MBCS, ISP, Member of IEEE, Professional Member of ACM. Research Interests: Collaborative Learning, Web 2.0, Web 3.0, Social Networking, Multimedia Learning Objects.

Prof. Sabah Mohammed

Affiliation not supplied
Thunder Bay, Ontario, Canada

Lyle Chamarette

Affiliation not supplied
Thunder Bay, Ontario, Canada

Ref: L09P1299