Advanced Data Mining and Applications

Second International Conference, ADMA 2006, Xi’an, China, August 14-16, 2006 Proceedings

  • Xue Li
  • Osmar R. Zaïane
  • Zhanhuai Li
Conference proceedings ADMA 2006

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4093)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 4093)

Table of contents

  1. Front Matter
    PDF

  2. Invited Papers

    1. Warehousing and Mining Massive RFID Data Sets
      Jiawei Han, Hector Gonzalez, Xiaolei Li, Diego Klabjan
      Pages 1-18
    2. Self-organising Map Techniques for Graph Data Applications to Clustering of XML Documents
      A. C. Tsoi, M. Hagenbuchner, A. Sperduti
      Pages 19-30
    3. Finding Time Series Discords Based on Haar Transform
      Ada Wai-chee Fu, Oscar Tat-Wing Leung, Eamonn Keogh, Jessica Lin
      Pages 31-41
    4. Learning with Local Drift Detection
      João Gama, Gladys Castillo
      Pages 42-55

  3. Association Rules

    1. A Fast Algorithm for Maintenance of Association Rules in Incremental Databases
      Xin Li, Zhi-Hong Deng, Shiwei Tang
      Pages 56-63
    2. Extending OLAP with Fuzziness for Effective Mining of Fuzzy Multidimensional Weighted Association Rules
      Mehmet Kaya, Reda Alhajj
      Pages 64-71
    3. Incremental Maintenance of Association Rules Based on Multiple Previously Mined Results
      Zhuohua Duan, Zixing Cai, Yan Lv
      Pages 72-79
    4. Mining and Validation of Localized Frequent Web Access Patterns with Dynamic Tolerance
      Olfa Nasraoui, Suchandra Goswami
      Pages 80-91
    5. SA-IFIM: Incrementally Mining Frequent Itemsets in Update Distorted Databases
      Jinlong Wang, Congfu Xu, Hongwei Dan, Yunhe Pan
      Pages 92-99
    6. Study of Positive and Negative Association Rules Based on Multi-confidence and Chi-Squared Test
      Xiangjun Dong, Fengrong Sun, Xiqing Han, Ruilian Hou
      Pages 100-109
    7. Efficiently Mining Maximal Frequent Mutually Associated Patterns
      Zhongmei Zhou, Zhaohui Wu, Chunshan Wang, Yi Feng
      Pages 110-117
    8. Efficiently Mining Mutually and Positively Correlated Patterns
      Zhongmei Zhou, Zhaohui Wu, Chunshan Wang, Yi Feng
      Pages 118-125

  4. Classification

    1. ComEnVprs: A Novel Approach for Inducing Decision Tree Classifiers
      Shuqin Wang, Jinmao Wei, Junping You, Dayou Liu
      Pages 126-134
    2. Towards a Rough Classification of Business Travelers
      Rob Law, Thomas Bauer, Karin Weber, Tony Tse
      Pages 135-142
    3. Feature Extraction Based on Optimal Discrimination Plane in ECG Signal Classification
      Dingfei Ge, Xiao Qu
      Pages 143-149
    4. Music Style Classification with a Novel Bayesian Model
      Yatong Zhou, Taiyi Zhang, Jiancheng Sun
      Pages 150-156
    5. Classification of Polarimetric SAR Data Based on Multidimensional Watershed Clustering
      Wen Yang, Hao Wang, Yongfeng Cao, Haijian Zhang
      Pages 157-164
    6. An Effective Combination Based on Class-Wise Expertise of Diverse Classifiers for Predictive Toxicology Data Mining
      Daniel Neagu, Gongde Guo, Shanshan Wang
      Pages 165-172
    7. Robust Collective Classification with Contextual Dependency Network Models
      Yonghong Tian, Tiejun Huang, Wen Gao
      Pages 173-180

About these proceedings

Keywords

Cluster Ubiquitous Computing Video Retrieval benchmarking bioinformatics classification correlation mining data mining data mining visualization disaster prediction e-commerce modeling ontology optimization performance tuning

Editors and affiliations

  • Xue Li
    • 1
  • Osmar R. Zaïane
    • 2
  • Zhanhuai Li
    • 3
  1. 1.School of Information Technology and Electronic EngineeringThe University of QueenslandAustralia
  2. 2.University of AlbertaCanada
  3. 3.Northwest Polytechnical UniversityChina

Bibliographic information

  • DOI https://doi.org/10.1007/11811305
  • Copyright Information Springer-Verlag Berlin Heidelberg 2006
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-540-37025-3
  • Online ISBN 978-3-540-37026-0
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book