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Advances in Knowledge Discovery and Data Mining

12th Pacific-Asia Conference, PAKDD 2008 Osaka, Japan, May 20-23, 2008 Proceedings

  • Conference proceedings
  • © 2008

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Editors:
  1. Takashi Washio
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  2. Einoshin Suzuki
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  3. Kai Ming Ting
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  4. Akihiro Inokuchi
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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 5012)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

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Conference proceedings info: PAKDD 2008.

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About this book

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.

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Table of contents (118 papers)

  1. Front Matter

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  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
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Other volumes

  1. Advances in Knowledge Discovery and Data Mining

  2. New Frontiers in Applied Data Mining

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