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Intelligent Information Processing II

IFIP TC12/WG12.3 International Conference on Intelligent Information Processing (IIP2004) October 21-23, 2004, Beijing, China

  • Conference proceedings
  • © 2005

Overview

Editors:
  1. Zhongzhi Shi

    1. Instittue of Computing TechnologyKey, Laboratory of Int. Infor. Process., Chinese Academy of Sciences, Beijing, China

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  2. Qing He

    1. Instittue of Computing TechnologyKey, Laboratory of Int. Infor. Process., Chinese Academy of Sciences, Beijing, China

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  • Highlights current work in Asia in the field of intelligent information processing
  • Includes supplementary material: sn.pub/extras

Part of the book series: IFIP Advances in Information and Communication Technology (IFIPAICT, volume 163)

Included in the following conference series:

Conference proceedings info: IIP 2004.

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Table of contents (66 papers)

  1. Front Matter

    Pages i-xxvii
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  2. Model Organization Constraints in Multi-Agent System

    • Xinjun Mao, Jiajia Chen
    Pages 1-10

  3. A Multi-Agent System for Mobile Environments

    • Jianwen Chen, Yan Zhang
    Pages 11-22

  4. Agent Interaction Management and Application in a Virtual Collaborative Environment

    • Aizhong Lin, Igor T. Hawryszkiewycz, Brian Henderson-Sellers
    Pages 23-36

  5. An Integrated Approach to Battlefield Situation Assessment

    • Yang Fan, Chang Guocen, Duan Tao, Hua Wenjian
    Pages 37-44

  6. Negotiation Based on Personality

    • Hong Zhang, Yuhui Qiu
    Pages 45-49

  7. MIAM: A Robot Oriented Mobile Intelligent Agent Model

    • Wu Shandong, Chen Yimin
    Pages 51-54

  8. Incorporating Elements from Camle in the Open Repository

    • C. Gonzalez-Perez, B. Henderson-Sellers, J. Debenham, G. C. Low, Q. -N. N. Tran
    Pages 55-64

  9. Representing Human Spatial Behavior by Self-Organizing Networks

    • Takamitsu Mizutori, Kenji Kohiyama
    Pages 65-68

  10. Multi-Agent System Development Kit

    • Vladimir Gorodetski, Oleg Karsaev, Vladimir Samoilov, Victor Konushy, Evgeny Mankov, Alexey Malyshev
    Pages 69-78

  11. Limitations in Auml’s Roles Specification

    • Jean-Luc Koning, Ivan Romero Hernández
    Pages 79-82

  12. The Research of Geometric Constraint Soving Based on the Path Tracking Homotopy Iteration Method

    • Cao Chunhong, Lu Yinan, Li Wenhui
    Pages 83-92

  13. Fast Stereo Matching Method Using Edge Traction

    • Zheng-dong Liu, Ying-nan Zhao, Jing-yu Yang
    Pages 93-96

  14. Hybrid Color Image Segmentation Based Fully Automatic Chroma-Keying System with Cluttered Background

    • Li Shijin, Zhu Yuelong, Yang Qian, Liu Zhe
    Pages 97-106

  15. Research on Techniques of Approximate Recognition of Continuous Deformation of Images with Multi-Grey-Levels

    • Feng Zhi-quan, Li Yi, Qu Shou-ning
    Pages 107-116

  16. Recognition of Image with Natural Textures Based on Learning of Information Augmentation

    • Cheng Xian-Yi, Yuan Xiao Hua, Li Shu-Qin, Xian De-Shen
    Pages 117-123

  17. Improvements on CCA Model with Application to Face Recognition

    • Quan-Sen Sun, Mao-Long Yang, Pheng-Ann Heng, De-Sen Xia
    Pages 125-134

  18. Performance of Several Types of Median Filters in Spectral Domain

    • O. Uma Maheshwari, G. B. Vanisree, D. Ebenezer
    Pages 135-142

  19. Fuzzy and Rough Set

    • Hong Jing, Lu Jingui, Shi Feng
    Pages 143-146

  20. Algebraic Property of Rough Implication Based on Interval Structure

    • Xue Zhan-ao, He Hua-can, Ma Ying-cang
    Pages 147-152
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  1. Intelligent Information Processing II

Keywords

About this book

Data Mining is the process of posing queries and extracting useful information, patterns and trends previously unknown from large quantities of data [Thu, 00]. It is the process where intelligent tools are applied in order to extract data patterns [JM, 01]. This encompasses a number of different technical approaches, such as cluster analysis, learning classification and association rules, and finding dependencies. Agents are defined as software entities that perform some set of tasks on behalf of users with some degree of autonomy. This research work deals about developing a automated data mining system which encompasses the familiar data mining algorithms using intelligent agents in object oriented databases and proposing a framework. Because the data mining system uses the intelligent agents, a new user will be able to interact with the data mining system without much data mining technical knowledge. This system will automatically select the appropriate data mining technique and select the necessary field needed from the database at the appropriate time without expecting the users to specify the specific technique and the parameters. Also a new framework is proposed for incorporating intelligent agents with automated data mining. One of the major goals in developing this system is to give the control to the computer for learning automatically by using intelligent agents.

Editors and Affiliations

  • Instittue of Computing TechnologyKey, Laboratory of Int. Infor. Process., Chinese Academy of Sciences, Beijing, China

    Zhongzhi Shi, Qing He

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