Advertisement

Birds Bring Flues? Mining Frequent and High Weighted Cliques from Birds Migration Networks

  • MingJie Tang
  • Weihang Wang
  • Yexi Jiang
  • Yuanchun Zhou
  • Jinyan Li
  • Peng Cui
  • Ying Liu
  • Baoping Yan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5982)

Abstract

Recent advances in satellite tracking technologies can provide huge amount of data for biologists to understand continuous long movement patterns of wild bird species. In particular, highly correlated habitat areas are of great biological interests. Biologists can use this information to strive potential ways for controlling highly pathogenic avian influenza. We convert these biological problems into graph mining problems. Traditional models for frequent graph mining assign each vertex label with equal weight. However, the weight difference between vertexes can make strong impact on decision making by biologists. In this paper, by considering different weights of individual vertex in the graph, we develop a new algorithm, Helen, which focuses on identifying cliques with high weights. We introduce “graph-weighted support framework” to reduce clique candidates, and then filter out the low weighted cliques. We evaluate our algorithm on real life birds’ migration data sets, and show that graph mining can be very helpful for ecologists to discover unanticipated bird migration relationships.

Keywords

Graph Mining Birds Migration Birds Flues H5N1 Scientific data Qinghai Lake 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Liu, J., et al.: Highly pathogenic H5N1 influenza virus infection in migratory birds. Science 309, 1206 (2005)CrossRefGoogle Scholar
  2. 2.
    Tang, M., Zhou, Y., Cui, P., Wang, W., Li, J., Zhang, H., Hou, Y., Yan, B.: Discovery of Migration Habitats and Routes of Wild Bird Species by Clustering and Association Analysis. In: Huang, R., Yang, Q., Pei, J., Gama, J., Meng, X., Li, X. (eds.) ADMA2009. LNCS, vol. 5678, pp. 288–301. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  3. 3.
    Wang, J., Zeng, Z., Zhou, L.: CLAN: An Algorithm for Mining Closed Cliques From Large Dense Graph Databases. In: ICDE 2006 (2006)Google Scholar
  4. 4.
    Zeng, Z., Wang, J., Zhou, L., Karypis, G.: Coherent closed quasi-clique discovery from large dense graph databases. In: SIGKDD 2006 (2006)Google Scholar
  5. 5.
    Pei, J., et al.: Mining Cross-graph Quasi-cliques in Gene Expression and Protein Interaction Data. In: ICDE 2005 (2005)Google Scholar
  6. 6.
    Ying, L., Liao, Choudhary, A.: A Fast High Utility Itemsets Mining Algorithm. In: UBDM 2005 (2005)Google Scholar
  7. 7.
    Tao, F., et al.: Weighted Association Rule Mining using Weighted Support and Significance Framework. In: SIGKDD 2003 (2003)Google Scholar
  8. 8.
    Agrawal, R., Srikant, R.: Fast Algorithms for Mining Association Rules. In: Proc. of the 20th VLDB Conference (1994)Google Scholar
  9. 9.
    Li, et al.: Numbers and distribution of waterbirds and wetlands in the Asia-Pacific region: results of the Asian Waterbird Census Wetlands International (2007)Google Scholar
  10. 10.
    Newman, S.H., Iverson, S.A., et al.: Migration of Whooper Swans and Outbreaks of Highly Pathogenic Avian Influenza H5N1 Virus in Eastern Asia. PLos ONE 4(5) (May 2009)Google Scholar
  11. 11.
    Sturm-Ramirez, K.M., Hulse-Post, D.J., Govorkova, E.A., Humberd, J., Seiler, P., et al.: Are ducks contributing to the endemicity of highly pathogenic H5N1influenza virus in Asia? J. Virol. 79, 11269–11279 (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • MingJie Tang
    • 1
    • 3
  • Weihang Wang
    • 1
    • 3
  • Yexi Jiang
    • 5
  • Yuanchun Zhou
    • 1
  • Jinyan Li
    • 4
  • Peng Cui
    • 2
    • 3
  • Ying Liu
    • 3
  • Baoping Yan
    • 1
  1. 1.Computer Network Information CenterChinese Academy of Sciences 
  2. 2.Institute of ZoologyChinese Academy of Sciences 
  3. 3.Graduate University of Chinese Academy of Sciences 
  4. 4.School of Computer EngineeringNanyang Technological University 
  5. 5.School of Computer ScienceSichuan UniversityChengdu

Personalised recommendations