Article ID: | iaor201112698 |
Volume: | 27 |
Issue: | 3 |
Start Page Number: | 458 |
End Page Number: | 488 |
Publication Date: | Aug 2011 |
Journal: | Computational Intelligence |
Authors: | Yeung Ching-man Au, Noll Michael G, Gibbins Nicholas, Meinel Christoph, Shadbolt Nigel |
Keywords: | collaboration systems, ranking |
In this article, we discuss the notions of experts and expertise in resource
discovery in the context of collaborative tagging systems. We propose that the
level of expertise of a user with respect to a particular topic is mainly
determined by two factors. First, an expert should possess a high-quality
collection of resources, while the quality of a Web resource in turn depends on
the expertise of the users who have assigned tags to it, forming a mutual
reinforcement relationship. Second, an expert should be one who tends to
identify interesting or useful resources before other users discover them, thus
bringing these resources to the attention of the community of users. We propose
a graph-based algorithm,