Skip to main content

Speeding Up Bipartite Graph Visualization Method

  • Conference paper
AI 2011: Advances in Artificial Intelligence (AI 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7106))

Included in the following conference series:

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Chung, F.R.K.: Spectral Graph Theory. CBMS Regional Conference Series in Mathematics, vol. (92). American Mathematical Society (February 1997)

    Google Scholar 

  2. Kamada, T., Kawai, S.: An algorithm for drawing general undirected graphs. Inf. Process. Lett. 31, 7–15 (1989)

    Article  MathSciNet  MATH  Google Scholar 

  3. Kleinberg, J.M.: Authoritative sources in a hyperlinked environment. J. ACM 46, 604–632 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  4. Langville, A.N., Meyer, C.D.: Deeper inside pagerank. Internet Mathematics 1 (2004)

    Google Scholar 

  5. Naud, A.P., Usui, S., Ueda, N., Taniguchi, T.: Visualization of documents and concepts in neuroinformatics with the 3d-se viewer. Frontiers in Neuroinformatics 1, Article 7 (2007)

    Google Scholar 

  6. Torgerson, W.S.: Theory and methods of scaling. John Wiley & Sons Inc. (1958)

    Google Scholar 

  7. Yamada, T., Saito, K., Ueda, N.: Cross-entropy directed embedding of network data. In: Proceedings of the 20th International Conference on Machine Learning (ICML 2003), pp. 832–839 (2003)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Fushimi, T., Kubota, Y., Saito, K., Kimura, M., Ohara, K., Motoda, H. (2011). Speeding Up Bipartite Graph Visualization Method. In: Wang, D., Reynolds, M. (eds) AI 2011: Advances in Artificial Intelligence. AI 2011. Lecture Notes in Computer Science(), vol 7106. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25832-9_71

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-25832-9_71

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25831-2

  • Online ISBN: 978-3-642-25832-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics