Detecting Some Collaborative Academic Indicators Based on Social Networks: A DBLP Case Study

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Fiaidhi, J. & Mohammed, S. (2008). Detecting Some Collaborative Academic Indicators Based on Social Networks: A DBLP Case Study. In J. Luca & E. Weippl (Eds.), Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications 2008 (pp. 6150-6157). Chesapeake, VA: AACE.
Retrieved from http://www.editlib.org/p/29234.

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Conference Information

World Conference on Educational Multimedia, Hypermedia and Telecommunications (EDMEDIA) 2008
Vienna, Austria
June 30, 2008
ISBN 1-880094-65-7
  Joseph Luca & Edgar R. Weippl
AACE

More Information on EDMEDIA
Table of Contents

Authors

Jinan Fiaidhi, Sabah Mohammed, Lakehead University, Canada

Abstract

Academia is focusing their attention on information retrieval over semantic metadata extracted from the Web, and it is increasingly possible to analyze such metadata to discover interesting relationships. However, just as document ranking is a critical component in today's traditional search engines, the ranking of complex relationships will be an important component in tomorrow's Semantic Web engines. This article presents a a ranking approach based on social networking to identify interesting and relevant relationships in a semantically represented XML open source data. This article presents an approach to analyze DBLP publications using Social Networking Reasoners.

Keywords

• Computer Sciences
• Information Sciences
• Social Sciences
• Social Studies
• Networking Technologies

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