Advanced Data Mining and Applications

Third International Conference, ADMA 2007 Harbin, China, August 6-8, 2007. Proceedings

  • Reda Alhajj
  • Hong Gao
  • Jianzhong Li
  • Xue Li
  • Osmar R. Zaïane

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4632)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 4632)

Table of contents

  1. Front Matter
  2. Invited Talk

  3. Regular Papers

    1. Renpu Li, Yongsheng Zhao, Fuzeng Zhang, Lihua Song
      Pages 35-44
    2. Zhitang Li, Aifang Zhang, Dong Li, Li Wang
      Pages 45-56
    3. K. Anil Kumar, C. Pandu Rangan
      Pages 57-68
    4. Chuang-Cheng Chiu, Chieh-Yuan Tsai
      Pages 89-99
    5. Xuhui Wang, Shengguo Huang, Li Cao, Dinghao Shi, Ping Shu
      Pages 100-109
    6. Jing Peng, Chang-jie Tang, Dong-qing Yang, An-long Chen, Lei Duan
      Pages 110-121
    7. Xiangjun Dong, Zhendong Niu, Xuelin Shi, Xiaodan Zhang, Donghua Zhu
      Pages 122-133
    8. Liangxiao Jiang, Dianhong Wang, Zhihua Cai, Xuesong Yan
      Pages 134-145
    9. Kejia Zhang, Shengfei Shi, Hong Gao, Jianzhong Li
      Pages 158-169
    10. Huaqiang Yuan, Yaxun Wang, Jie Zhang, Wei Tan, Chao Qu, Wenbin He
      Pages 183-190

About these proceedings


The Third International Conference on Advanced Data Mining and Applications (ADMA) organized in Harbin, China continued the tradition already established by the first two ADMA conferences in Wuhan in 2005 and Xi’an in 2006. One major goal of ADMA is to create a respectable identity in the data mining research com- nity. This feat has been partially achieved in a very short time despite the young age of the conference, thanks to the rigorous review process insisted upon, the outstanding list of internationally renowned keynote speakers and the excellent program each year. The impact of a conference is measured by the citations the conference papers receive. Some have used this measure to rank conferences. For example, the independent source ranks ADMA (0.65) higher than PAKDD (0.64) and PKDD (0.62) as of June 2007, which are well established conferences in data mining. While the ranking itself is questionable because the exact procedure is not disclosed, it is nevertheless an encouraging indicator of recognition for a very young conference such as ADMA.


Attribut Bayesian networks Business-Intelligence Fusion algorithms bioinformatics classification correlation mining data mining feature selection genomics indexing intelligence learning statistics

Editors and affiliations

  • Reda Alhajj
    • 1
  • Hong Gao
    • 2
  • Jianzhong Li
    • 3
  • Xue Li
    • 4
  • Osmar R. Zaïane
    • 5
  1. 1.Computer Science DepartmentUniversity of Calgary CalgaryCanada
  2. 2.School of Computer Science and Technology Harbin Institute of TechnologyHarbinChina
  3. 3.School of Computer Science and Technology Harbin Institute of Technology HarbinChina
  4. 4.School of Information Technology and Electronic Engineering The University of Queensland QueenslandAustralia
  5. 5.Department of Computing Science University of AlbertaEdmontonCanada

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2007
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-540-73870-1
  • Online ISBN 978-3-540-73871-8
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book