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Published in:
2011 | OriginalPaper | Chapter
Speeding Up Bipartite Graph Visualization Method
Authors : Takayasu Fushimi, Yamato Kubota, Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda
Published in: AI 2011: Advances in Artificial Intelligence
Publisher: Springer Berlin Heidelberg
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We address the problem of visualizing structure of bipartite graphs such as relations between pairs of objects and their multi-labeled categories. For this task, the existing spherical embedding method, as well as the other standard graph embedding methods, can be used. However, these existing methods either produce poor visualization results or require extremely large computation time to obtain the final results. In order to overcome these shortcomings, we propose a new spherical embedding method based on a power iteration, which additionally performs two operations on the position vectors: double-centering and normalizing operations. Moreover, we theoretically prove that the proposed method always converges. In our experiments using bipartite graphs constructed from the Japanese sites of Yahoo!Movies and Yahoo!Answers, we show that the proposed method works much faster than these existing methods and still the visualization results are comparable to the best available so far.