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  • Conference proceedings
  • © 2010

Advanced Data Mining and Applications

6th International Conference, ADMA 2010, Chongqing, China, November 19-21, 2010, Proceedings, Part II

Editors:

  1. Longbing Cao

    1. Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, Australia

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    You can also search for this editor in PubMed   Google Scholar

  2. Jiang Zhong

    1. College of Computer Science, Chongqing University, Chongqing, China

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    You can also search for this editor in PubMed   Google Scholar

  3. Yong Feng

    1. College of Computer Science, Chongqing University, Chongqing, China

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 6441)

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

Conference series link(s): ADMA: International Conference on Advanced Data Mining and Applications

Conference proceedings info: ADMA 2010.

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Table of contents (58 papers)

  1. Front Matter

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  2. III Data Mining Methodologies and Processes

    1. Incremental Learning by Heterogeneous Bagging Ensemble

      • Qiang Li Zhao, Yan Huang Jiang, Ming Xu
      Pages 1-12

    2. CPLDP: An Efficient Large Dataset Processing System Built on Cloud Platform

      • Zhiyong Zhong, Mark Li, Jin Chang, Le Zhou, Joshua Zhexue Huang, Shengzhong Feng
      Pages 13-20

    3. A General Multi-relational Classification Approach Using Feature Generation and Selection

      • Miao Zou, Tengjiao Wang, Hongyan Li, Dongqing Yang
      Pages 21-33

    5. A Clustering-Based Data Reduction for Very Large Spatio-Temporal Datasets

      • Nhien-An Le-Khac, Martin Bue, Michael Whelan, M-Tahar Kechadi
      Pages 43-54

    6. Change a Sequence into a Fuzzy Number

      • Diana DomaÅ„ska, Marek Wojtylak
      Pages 55-62

    7. Multiple Kernel Learning Improved by MMD

      • Jiangtao Ren, Zhou Liang, Shaofeng Hu
      Pages 63-74

    8. A Refinement Approach to Handling Model Misfit in Semi-supervised Learning

      • Hanjing Su, Ling Chen, Yunming Ye, Zhaocai Sun, Qingyao Wu
      Pages 75-86

    9. Soft Set Approach for Selecting Decision Attribute in Data Clustering

      • Mohd Isa Awang, Ahmad Nazari Mohd Rose, Tutut Herawan, Mustafa Mat Deris
      Pages 87-98

    10. Comparison of BEKK GARCH and DCC GARCH Models: An Empirical Study

      • Yiyu Huang, Wenjing Su, Xiang Li
      Pages 99-110

    12. Evaluating the Distance between Two Uncertain Categorical Objects

      • Hongmei Chen, Lizhen Wang, Weiyi Liu, Qing Xiao
      Pages 122-133

    14. Spatial Filter Selection with LASSO for EEG Classification

      • Wenting Tu, Shiliang Sun
      Pages 142-149

    15. Boolean Algebra and Compression Technique for Association Rule Mining

      • Somboon Anekritmongkol, M. L. Kulthon Kasamsan
      Pages 150-157

    16. Cluster Based Symbolic Representation and Feature Selection for Text Classification

      • B. S. Harish, D. S. Guru, S. Manjunath, R. Dinesh
      Pages 158-166

    18. Logistic Regression for Transductive Transfer Learning from Multiple Sources

      • Yuhong Zhang, Xuegang Hu, Yucheng Fang
      Pages 175-182

    19. Double Table Switch: An Efficient Partitioning Algorithm for Bottom-Up Computation of Data Cubes

      • Jinguo You, Lianying Jia, Jianhua Hu, Qingsong Huang, Jianqing Xi
      Pages 183-190
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Other Volumes

  1. Advanced Data Mining and Applications

  2. Advanced Data Mining and Applications

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About this book

With the ever-growing power of generating, transmitting, and collecting huge amounts of data, information overloadis nowan imminent problemto mankind. The overwhelming demand for information processing is not just about a better understanding of data, but also a better usage of data in a timely fashion. Data mining, or knowledge discovery from databases, is proposed to gain insight into aspects ofdata and to help peoplemakeinformed,sensible,and better decisions. At present, growing attention has been paid to the study, development, and application of data mining. As a result there is an urgent need for sophisticated techniques and toolsthat can handle new ?elds of data mining, e. g. , spatialdata mining, biomedical data mining, and mining on high-speed and time-variant data streams. The knowledge of data mining should also be expanded to new applications. The 6th International Conference on Advanced Data Mining and Appli- tions(ADMA2010)aimedtobringtogethertheexpertsondataminingthrou- out the world. It provided a leading international forum for the dissemination of original research results in advanced data mining techniques, applications, al- rithms, software and systems, and di?erent applied disciplines. The conference attracted 361 online submissions from 34 di?erent countries and areas. All full papers were peer reviewed by at least three members of the Program Comm- tee composed of international experts in data mining ?elds. A total number of 118 papers were accepted for the conference. Amongst them, 63 papers were selected as regular papers and 55 papers were selected as short papers.
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Keywords

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Editors and Affiliations

  • Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, Australia

    Longbing Cao

  • College of Computer Science, Chongqing University, Chongqing, China

    Jiang Zhong, Yong Feng

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Bibliographic Information

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Buy it now

eBook USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

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