Real-world social networks are often hierarchical, reflecting the fact that some communities are composed of a few smaller, sub-communities. This paper describes a hierarchical B...
Haizheng Zhang, Wei Li, Xuerui Wang, C. Lee Giles,...
This paper employs the network perspective to study patterns and structures of intraorganizational learning networks. The theoretical background draws from cognitive theories, the...
Recently, a number of algorithms have been proposed to obtain hierarchical structures — so-called folksonomies — from social tagging data. Work on these algorithms is in part ...
Denis Helic, Markus Strohmaier, Christoph Trattner...
One of the most widely used techniques for data clustering is agglomerative clustering. Such algorithms have been long used across many different fields ranging from computational...