Intelligent Information Processing II

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

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.

• Constraint Satisfaction
• Mapping
• bioinformatics
• case-based reasoning
• classification
• data structure
• hardware
• information system
• machine learning
• multi-agent system
• optimization
• programming
• robot
• service-oriented computing
• uncertain reasoning

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

  Zhongzhi Shi, Qing He

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