Mining Research Communities in Bibliographical Data

Authors:
Osmar R. Zaïane;Jiyang Chen;Randy Goebel
Affiliations:
University of Alberta, Canada;University of Alberta, Canada;University of Alberta, Canada
Venue:
Advances in Web Mining and Web Usage Analysis
Year:
2009

Citing 16
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Abstract

Extracting information from very large collections of structured, semi-structured or even unstructured data can be a considerable challenge when much of the hidden information is implicit within relationships among entities in the data. Social networks are such data collections in which relationships play a vital role in the knowledge these networks can convey. A bibliographic database is an essential tool for the research community, yet finding and making use of relationships comprised within such a social network is difficult. In this paper we introduce DBconnect, a prototype that exploits the social network coded within the DBLP database by drawing on a new random walk approach to reveal interesting knowledge about the research community and even recommend collaborations.