Detecting Some Collaborative Academic Indicators Based on Social Networks: A DBLP Case Study PROCEEDINGS
Jinan Fiaidhi, Sabah Mohammed, Lakehead University, Canada
EdMedia + Innovate Learning, in Vienna, Austria ISBN 978-1-880094-65-5 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC
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.
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 ED-MEDIA 2008--World Conference on Educational Multimedia, Hypermedia & Telecommunications (pp. 6150-6157). Vienna, Austria: Association for the Advancement of Computing in Education (AACE). Retrieved November 16, 2018 from https://www.learntechlib.org/primary/p/29234/.
© 2008 Association for the Advancement of Computing in Education (AACE)
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