Advances in Knowledge Discovery and Data Mining

1. Front Matter

   PDF

2. Keynote Speech

   1. Graph Mining: Laws, Generators and Tools

      • Christos Faloutsos

      Pages 1-1

3. Invited Speeches

   1. Efficient Algorithms for Mining Frequent and Closed Patterns from Semi-structured Data

      • Hiroki Arimura

      Pages 2-13

   2. Supporting Creativity: Towards Associative Discovery of New Insights

      • Michael R. Berthold, Fabian Dill, Tobias Kötter, Kilian Thiel

      Pages 14-25

   3. Cost-Sensitive Classifier Evaluation Using Cost Curves

      • Robert C. Holte, Chris Drummond

      Pages 26-29

   4. Prospective Scientific Methodology in Knowledge Society

      • Genshiro Kitagawa

      Pages 30-39

4. Long Papers

   1. SubClass: Classification of Multidimensional Noisy Data Using Subspace Clusters

      • Ira Assent, Ralph Krieger, Petra Welter, Jörg Herbers, Thomas Seidl

      Pages 40-52

   2. Mining Quality-Aware Subspace Clusters

      • Ying-Ju Chen, Yi-Hong Chu, Ming-Syan Chen

      Pages 53-63

   3. A Decremental Approach for Mining Frequent Itemsets from Uncertain Data

      • Chun-Kit Chui, Ben Kao

      Pages 64-75

   4. Multi-class Named Entity Recognition Via Bootstrapping with Dependency Tree-Based Patterns

      • Van B. Dang, Akiko Aizawa

      Pages 76-87

   5. Towards Region Discovery in Spatial Datasets

      • Wei Ding, Rachsuda Jiamthapthaksin, Rachana Parmar, Dan Jiang, Tomasz F. Stepinski, Christoph F. Eick

      Pages 88-99

   6. Accurate and Efficient Retrieval of Multimedia Time Series Data Under Uniform Scaling and Time Warping

      • Waiyawuth Euachongprasit, Chotirat Ann Ratanamahatana

      Pages 100-111

   7. Feature Construction Based on Closedness Properties Is Not That Simple

      • Dominique Gay, Nazha Selmaoui, Jean-François Boulicaut

      Pages 112-123

   8. On Addressing Accuracy Concerns in Privacy Preserving Association Rule Mining

      • Ling Guo, Songtao Guo, Xintao Wu

      Pages 124-135

   9. Privacy-Preserving Linear Fisher Discriminant Analysis

      • Shuguo Han, Wee Keong Ng

      Pages 136-147

   10. Unsupervised Change Analysis Using Supervised Learning

       • Shohei Hido, Tsuyoshi Idé, Hisashi Kashima, Harunobu Kubo, Hirofumi Matsuzawa

       Pages 148-159

   11. ANEMI: An Adaptive Neighborhood Expectation-Maximization Algorithm with Spatial Augmented Initialization

       • Tianming Hu, Hui Xiong, Xueqing Gong, Sam Yuan Sung

       Pages 160-171

   12. Minimum Variance Associations — Discovering Relationships in Numerical Data

       • Szymon Jaroszewicz

       Pages 172-183

   13. An Efficient Unordered Tree Kernel and Its Application to Glycan Classification

       • Tetsuji Kuboyama, Kouichi Hirata, Kiyoko F. Aoki-Kinoshita

       Pages 184-195

   14. Generation of Globally Relevant Continuous Features for Classification

       • Sylvain Létourneau, Stan Matwin, A. Fazel Famili

       Pages 196-208

ThePaci?c-AsiaConferenceonKnowledgeDiscoveryandDataMining(PAKDD) has been held every year since 1997. PAKDD 2008, the 12th in the series, was heldatOsaka,JapanduringMay20–23,2008.PAKDDisaleadinginternational conference in the area of data mining. It provides an international forum for - searchers and industry practitioners to share their new ideas, original research results, and practical development experiences from all KDD-related areas - cluding data mining, data warehousing, machine learning, databases, statistics, knowledge acquisition, automatic scienti?c discovery, data visualization, causal induction, and knowledge-based systems. This year we received a total of 312 research papers from 34 countries and regions in Asia, Australia, North America, South America, Europe, and Africa. Every submitted paper was rigorously reviewed by two or three reviewers, d- cussed by the reviewers under the supervision of an Area Chair, and judged by the Program Committee Chairs. When there was a disagreement, the Area Chair and/or the Program Committee Chairs provided an additional review. Thus, many submissions were reviewed by four experts. The Program Comm- tee members were deeply involved in a highly selective process. As a result, only approximately11.9%ofthe312submissionswereacceptedaslongpapers,12.8% of them were accepted as regular papers, and 11.5% of them were accepted as short papers.

• data mining
• data warehouse
• database
• databases
• knowledge
• knowledge discovery
• knowledge-based system
• knowledge-based systems
• learning
• machine learning
• statistics
• visualization
• warehousing

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