A Multi-Agent method for parallel mining based on rough sets

被引:0
|
作者
Geng, Zhiqiang [1 ]
Zhu, Qunxiong [1 ]
机构
[1] Beijing Univ Chem Technol, Sch Informat Sci & Technol, Beijing 100029, Peoples R China
来源
WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS | 2006年
关键词
rough set; data mining; Multi-agent; parallel mining;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Rough set is a relatively new AI technique in data mining. Multi-Agent system (MAS) has become a hotspot in the field of distributed AI recently. The challenge of the information age yet has not been resolved and the decision can't be made precisely and in time according to market and requirements. To improve the performing efficiency of data mining system, the paper defines the novel operations and reasoning of agents and a Multi-Agent method for parallel rule mining based on Rough sets is proposed. The information system is decomposed into many sub-information systems and every sub-information system can be an agent using rough set to acquire rules. From results of parallel mining, decisions can be made quickly and precisely.
引用
收藏
页码:5977 / +
页数:2
相关论文
共 50 条
  • [21] Distributed data mining system based on multi-agent technology
    Guo, Li-Ming
    Zhang, Yan-Zhen
    Journal of Donghua University (English Edition), 2006, 23 (06) : 80 - 83
  • [22] Modelling Multi-agent Three-way Decisions with Decision-theoretic Rough Sets
    Yang, Xiaoping
    Yao, JingTao
    FUNDAMENTA INFORMATICAE, 2012, 115 (2-3) : 157 - 171
  • [23] A Parallel Decomposition Method for Nonconvex Stochastic Multi-Agent Optimization Problems
    Yang, Yang
    Scutari, Gesualdo
    Palomar, Daniel P.
    Pesavento, Marius
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2016, 64 (11) : 2949 - 2964
  • [24] Research on a Novel Data Mining Method Based on the Rough Sets and Neural Network
    Jiang, Weijin
    Xu, Yusheng
    He, Jing
    Shi, Dejia
    Xu, Yuhui
    ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE, PROCEEDINGS, 2009, 5855 : 639 - +
  • [25] Distributed Data Mining System Based on Multi-agent Communication Mechanism
    Kim, Sung Gook
    Woo, Kyeong Deok
    Bala, Jerzy
    Baik, Sung Wook
    AGENT AND MULTI-AGENT SYSTEMS: TECHNOLOGIES AND APPLICATIONS, PT II, PROCEEDINGS, 2010, 6071 : 100 - +
  • [26] A Multi-Agent Based Model for User Interest Mining on Sina Weibo
    Meijia Wang
    Qingshan Li
    ChinaCommunications, 2022, 19 (02) : 225 - 234
  • [27] Sampling based Multi-Agent Joint Learning for Association Rule Mining
    Xu, Junyi
    Yao, Li
    Li, Le
    Chen, Yifan
    AAMAS'14: PROCEEDINGS OF THE 2014 INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS & MULTIAGENT SYSTEMS, 2014, : 1469 - 1470
  • [28] A Multi-Agent Based Decentralized Algorithm for Social Network Community Mining
    Yang, Bo
    Huang, Jing
    Liu, Dayou
    Liu, Jiming
    2009 INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING, 2009, : 78 - +
  • [29] A multi-agent based model for user interest mining on Sina Weibo
    Wang, Meijia
    Li, Qingshan
    CHINA COMMUNICATIONS, 2022, 19 (02) : 225 - 234
  • [30] A Framework for Data Mining Based Multi-Agent: An Application to Spatial Data
    Zghal, H. Baazaoui
    Faiz, S.
    Ben Ghezala, H.
    PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 5, 2005, 5 : 22 - 26