Advances in Knowledge Discovery and Data Mining

1. Front Matter

   PDF

2. Keynote Speech

   1. Protection or Privacy? Data Mining and Personal Data

      • David J. Hand

      Pages 1-10

   2. The Changing Face of Web Search

      • Prabhakar Raghavan

      Pages 11-11

3. Invited Speech

   1. Data Mining for Surveillance Applications

      • Bhavani M. Thuraisingham

      Pages 12-14

4. Classification

   1. A Multiclass Classification Method Based on Output Design

      • Qi Qiang, Qinming He

      Pages 15-19

   2. Regularized Semi-supervised Classification on Manifold

      • Lianwei Zhao, Siwei Luo, Yanchang Zhao, Lingzhi Liao, Zhihai Wang

      Pages 20-29

   3. Similarity-Based Sparse Feature Extraction Using Local Manifold Learning

      • Cheong Hee Park

      Pages 30-34

   4. Generalized Conditional Entropy and a Metric Splitting Criterion for Decision Trees

      • Dan A. Simovici, Szymon Jaroszewicz

      Pages 35-44

   5. RNBL-MN: A Recursive Naive Bayes Learner for Sequence Classification

      • Dae-Ki Kang, Adrian Silvescu, Vasant Honavar

      Pages 45-54

   6. TRIPPER: Rule Learning Using Taxonomies

      • Flavian Vasile, Adrian Silvescu, Dae-Ki Kang, Vasant Honavar

      Pages 55-59

   7. Using Weighted Nearest Neighbor to Benefit from Unlabeled Data

      • Kurt Driessens, Peter Reutemann, Bernhard Pfahringer, Claire Leschi

      Pages 60-69

   8. Constructive Meta-level Feature Selection Method Based on Method Repositories

      • Hidenao Abe, Takahira Yamaguchi

      Pages 70-80

5. Ensemble Learning

   1. Variable Randomness in Decision Tree Ensembles

      • Fei Tony Liu, Kai Ming Ting

      Pages 81-90

   2. Further Improving Emerging Pattern Based Classifiers Via Bagging

      • Hongjian Fan, Ming Fan, Kotagiri Ramamohanarao, Mengxu Liu

      Pages 91-96

   3. Improving on Bagging with Input Smearing

      • Eibe Frank, Bernhard Pfahringer

      Pages 97-106

   4. Boosting Prediction Accuracy on Imbalanced Datasets with SVM Ensembles

      • Yang Liu, Aijun An, Xiangji Huang

      Pages 107-118

6. Ensemble Learning

   1. DeLi-Clu: Boosting Robustness, Completeness, Usability, and Efficiency of Hierarchical Clustering by a Closest Pair Ranking

      • Elke Achtert, Christian Böhm, Peer Kröger

      Pages 119-128

   2. Iterative Clustering Analysis for Grouping Missing Data in Gene Expression Profiles

      • Dae-Won Kim, Bo-Yeong Kang

      Pages 129-138

   3. An EM-Approach for Clustering Multi-Instance Objects

      • Hans-Peter Kriegel, Alexey Pryakhin, Matthias Schubert

      Pages 139-148

   4. Mining Maximal Correlated Member Clusters in High Dimensional Database

      • Lizheng Jiang, Dongqing Yang, Shiwei Tang, Xiuli Ma, Dehui Zhang

      Pages 149-159

The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) is a leading international conference in the area of data mining and knowledge discovery. This year marks the tenth anniversary of the successful annual series of PAKDD conferences held in the Asia Pacific region. It was with pleasure that we hosted PAKDD 2006 in Singapore again, since the inaugural PAKDD conference was held in Singapore in 1997. PAKDD 2006 continues its tradition of providing an international forum for researchers and industry practitioners to share their new ideas, original research results and practical development experiences from all aspects of KDD data mining, including data cleaning, data warehousing, data mining techniques, knowledge visualization, and data mining applications. This year, we received 501 paper submissions from 38 countries and regions in Asia, Australasia, North America and Europe, of which we accepted 67 (13.4%) papers as regular papers and 33 (6.6%) papers as short papers. The distribution of the accepted papers was as follows: USA (17%), China (16%), Taiwan (10%), Australia (10%), Japan (7%), Korea (7%), Germany (6%), Canada (5%), Hong Kong (3%), Singapore (3%), New Zealand (3%), France (3%), UK (2%), and the rest from various countries in the Asia Pacific region.

• algorithms
• classification
• data mining
• database
• knowledge discovery
• learning
• multimedia
• relational database
• service-oriented computing
• web mining

• Nanyang Technological University, Singapore

  Wee-Keong Ng

• Institute of Industrial Science, The University of Tokyo, Tokyo, Japan

  Masaru Kitsuregawa

• School of Computer Science and Technology, Heilongjiang University, China

  Jianzhong Li

• School of Computer Engineering, Nanyang Technological University, Singapore, Singapore

  Kuiyu Chang

Policies and ethics