Abstract
In this paper, we propose a method that enables efficient extraction of hierarchical structure of Web communities containing Web videos that have similar topics in order to retrieve users’ desired Web videos. Specifically, the proposed method first calculates Web video features by applying canonical correlation analysis to a small number of Web video samples obtained on the basis of a clustering scheme. Furthermore, we construct a “community graph” of which each node consists of multiple Web videos and each edge corresponds to hyperlinks of Web pages including these videos. Then, based on strongly connected components, edge betweenness and modularity of the community graph, hierarchical structure of Web communities is estimated. In this way, our method can efficiently extract the hierarchical structure of Web communities, and users’ desired Web videos can be retrieved by selecting Web communities according to their hierarchical structure.
