Advances in Knowledge Discovery and Data Mining

1. Front Matter

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2. Feature Extraction

   1. An Instance Selection Algorithm Based on Reverse Nearest Neighbor

      • Bi-Ru Dai, Shu-Ming Hsu

      Pages 1-12

   2. A Game Theoretic Approach for Feature Clustering and Its Application to Feature Selection

      • Dinesh Garg, Sellamanickam Sundararajan, Shirish Shevade

      Pages 13-25

   3. Feature Selection Strategy in Text Classification

      • Pui Cheong Gabriel Fung, Fred Morstatter, Huan Liu

      Pages 26-37

   4. Unsupervised Feature Weighting Based on Local Feature Relatedness

      • Jiali Yun, Liping Jing, Jian Yu, Houkuan Huang

      Pages 38-49

   5. An Effective Feature Selection Method for Text Categorization

      • Xipeng Qiu, Jinlong Zhou, Xuanjing Huang

      Pages 50-61

3. Machine Learning

   1. A Subpath Kernel for Rooted Unordered Trees

      • Daisuke Kimura, Tetsuji Kuboyama, Tetsuo Shibuya, Hisashi Kashima

      Pages 62-74

   2. Classification Probabilistic PCA with Application in Domain Adaptation

      • Victor Cheng, Chun-Hung Li

      Pages 75-86

   3. Probabilistic Matrix Factorization Leveraging Contexts for Unsupervised Relation Extraction

      • Shingo Takamatsu, Issei Sato, Hiroshi Nakagawa

      Pages 87-99

   4. The Unsymmetrical-Style Co-training

      • Bin Wang, Harry Zhang, Bruce Spencer, Yuanyuan Guo

      Pages 100-111

   5. Balance Support Vector Machines Locally Using the Structural Similarity Kernel

      • Jianxin Wu

      Pages 112-123

   6. Using Classifier-Based Nominal Imputation to Improve Machine Learning

      • Xiaoyuan Su, Russell Greiner, Taghi M. Khoshgoftaar, Amri Napolitano

      Pages 124-135

   7. A Bayesian Framework for Learning Shared and Individual Subspaces from Multiple Data Sources

      • Sunil Kumar Gupta, Dinh Phung, Brett Adams, Svetha Venkatesh

      Pages 136-147

   8. Are Tensor Decomposition Solutions Unique? On the Global Convergence HOSVD and ParaFac Algorithms

      • Dijun Luo, Chris Ding, Heng Huang

      Pages 148-159

   9. Improved Spectral Hashing

      • Sanparith Marukatat, Wasin Sinthupinyo

      Pages 160-170

4. Clustering

   1. High-Order Co-clustering Text Data on Semantics-Based Representation Model

      • Liping Jing, Jiali Yun, Jian Yu, Joshua Huang

      Pages 171-182

   2. The Role of Hubness in Clustering High-Dimensional Data

      • Nenad Tomašev, Miloš Radovanović, Dunja Mladenić, Mirjana Ivanović

      Pages 183-195

   3. Spatial Entropy-Based Clustering for Mining Data with Spatial Correlation

      • Baijie Wang, Xin Wang

      Pages 196-208

   4. Self-adjust Local Connectivity Analysis for Spectral Clustering

      • Hui Wu, Guangzhi Qu, Xingquan Zhu

      Pages 209-224

   5. An Effective Density-Based Hierarchical Clustering Technique to Identify Coherent Patterns from Gene Expression Data

      • Sauravjyoti Sarmah, Rosy Das Sarmah, Dhruba Kumar Bhattacharyya

      Pages 225-236

The two-volume set LNAI 6634 and 6635 constitutes the refereed proceedings of the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2011, held in Shenzhen, China in May 2011. The total of 32 revised full papers and 58 revised short papers were carefully reviewed and selected from 331 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas including data mining, machine learning, artificial intelligence and pattern recognition, data warehousing and databases, statistics, knowledge engineering, behavior sciences, visualization, and emerging areas such as social network analysis.

• association rule mining
• classification
• clustering
• data analysis
• sequence analysis
• statistical learning
• text mining
• algorithm analysis and problem complexity

• Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences, Shenzhen, China

  Joshua Zhexue Huang

• Faculty of Engineering and Information Technology, Center for Quantum Computation and Intelligent Systems, Data Sciences and Knowledge Discovery Lab, University of Technology Sydney, Sydney, Australia

  Longbing Cao

• Department of Computer Science and Engineering, University of Minnesota, Minneapolis, USA

  Jaideep Srivastava

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