© 2008

Advanced Data Mining and Applications

4th International Conference, ADMA 2008, Chengdu, China, October 8-10, 2008. Proceedings

  • Changjie Tang
  • Charles X. Ling
  • Xiaofang Zhou
  • Nick J. Cercone
  • Xue Li
Conference proceedings ADMA 2008

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5139)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 5139)

Table of contents

  1. Front Matter
  2. Keynotes

  3. Regular Papers

    1. Frank Rehm, Frank Klawonn
      Pages 3-14
    2. Manolis Maragoudakis, Nikolaos Cosmas, Aristogiannis Garbis
      Pages 15-26
    3. Weijian Ni, Yalou Huang, Dong Li, Yang Wang
      Pages 27-38
    4. S. Chattopadhyay, P. Ray, H. S. Chen, M. B. Lee, H. C. Chiang
      Pages 51-61
    5. Hoai An Le Thi, Van Vinh Nguyen, Samir Ouchani
      Pages 62-72
    6. Shady Shehata, Fakhri Karray, Mohamed Kamel
      Pages 87-98
    7. Nattapon Harnsamut, Juggapong Natwichai, Xingzhi Sun, Xue Li
      Pages 111-122
    8. Jiangtao Qiu, Chuan Li, Shaojie Qiao, Taiyong Li, Jun Zhu
      Pages 123-134
    9. Savo Kordic, Peng Lam, Jitian Xiao, Huaizhong Li
      Pages 135-146
    10. Thanh-Nghi Do, Van-Hoa Nguyen, François Poulet
      Pages 147-157
    11. Yintian Liu, Yingming Liu, Tao Zeng, Kaikuo Xu, Rong Tang
      Pages 158-169
    12. Ji-Rong Sun, Zhi-Shu Li, Jian-Cheng Ni
      Pages 182-193

About these proceedings


This book constitutes the refereed proceedings of the 4th International Conference on Advanced Data Mining and Applications, ADMA 2008, held in Chengdu, China, in October 2008.

The 35 revised full papers and 43 revised short papers presented together with the abstract of 2 keynote lectures were carefully reviewed and selected from 304 submissions. The papers focus on advancements in data mining and peculiarities and challenges of real world applications using data mining and feature original research results in data mining, spanning applications, algorithms, software and systems, and different applied disciplines with potential in data mining.


Bayesian network Bayesian networks algorithms benchmarking classification correlation mining decision tree e-commerce information retrieval local learning maintenance ontology programming proving testing

Editors and affiliations

  • Changjie Tang
    • 1
  • Charles X. Ling
    • 2
  • Xiaofang Zhou
    • 3
  • Nick J. Cercone
    • 4
  • Xue Li
    • 5
  1. 1.School of Computer ScienceSichuan UniversityChengduChina
  2. 2.Department of Computer ScienceThe University of Western OntarioCanada
  3. 3.School of ITEEThe University of QueenslandAustralia
  4. 4.Faculty of Science & EngineeringYork UniversityTorontoCanada
  5. 5.School of Information Technology and Electrical EngineeringThe University of Queensland, BrisbaneQueenslandAustralia

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