Cluster-computer based incremental and distributed RSOM data-clustering

被引:0
|
作者
Xia, Sheng-Ping [1 ]
Liu, Jian-Jun [1 ]
Yuan, Zhen-Tao [1 ]
Yu, Hua [1 ]
Zhang, Le-Feng [1 ]
Yu, Wen-Xian [1 ]
机构
[1] Key Lab. of Automatic Target Recognition, National University of Defense Technology, Changsha 410073, China
来源
关键词
Computer systems - Data mining - Parallel algorithms - Parallel processing systems - Pattern recognition - Self organizing maps;
D O I
暂无
中图分类号
学科分类号
摘要
For large data-set with high dimensionality, of which the numbers of samples and patterns increase dynamically, in order to improve the computing-efficiency, it is necessary to design parallel incremental clustering algorithm. Noticing the nature of the human brain-an incremental studying style, and the hierarchical and distributed structure properties of a RSOM tree, a Cluster-computer system based incremental and distributed parallel algorithm of RSOM tree is proposed. The performance of this method is tested with the large feature data sets which are extracted from a large amount of video pictures.
引用
收藏
页码:385 / 391
相关论文
共 50 条
  • [1] A data-clustering algorithm on distributed memory multiprocessors
    Dhillon, IS
    Modha, DS
    LARGE-SCALE PARALLEL DATA MINING, 2000, 1759 : 245 - 260
  • [2] Cluster Feature-Based Incremental Clustering Approach (CFICA) For Numerical Data
    Sowjanya, A. M.
    Shashi, M.
    INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY, 2010, 10 (09): : 73 - 79
  • [3] A data-clustering approach based on artificial ant colonies with control of emergence
    Kenidra, Billel
    Meshoul, Souham
    2014 6TH INTERNATIONAL CONFERENCE OF SOFT COMPUTING AND PATTERN RECOGNITION (SOCPAR), 2014, : 209 - 214
  • [4] MapReduce-based Dragonfly Algorithm for large-scale Data-Clustering
    Tripathi, Ashish Kumar
    Saxena, Pranav
    Gupta, Siddharth
    2019 FIFTH INTERNATIONAL CONFERENCE ON IMAGE INFORMATION PROCESSING (ICIIP 2019), 2019, : 171 - 175
  • [5] Distributed and Incremental Clustering Based on Weighted Affinity Propagation
    Zhang, Xiangliang
    Furtlehner, Cyril
    Sebag, Michele
    STAIRS 2008, 2008, 179 : 199 - +
  • [6] Multiway-Based Weigh-in-Motion Data-Clustering Analysis for Pavement ME Design
    Yang, Guangwei
    Li, Qiang Joshua
    Wang, K. C. P.
    Fei, Yue
    Wang, Chaohui
    JOURNAL OF COMPUTING IN CIVIL ENGINEERING, 2017, 31 (05)
  • [7] An efficient incremental clustering based improved K-Medoids for IoT multivariate data cluster analysis
    Balakrishna, Sivadi
    Thirumaran, M.
    Padmanaban, R.
    Solanki, Vijender Kumar
    PEER-TO-PEER NETWORKING AND APPLICATIONS, 2020, 13 (04) : 1152 - 1175
  • [8] An efficient incremental clustering based improved K-Medoids for IoT multivariate data cluster analysis
    Sivadi Balakrishna
    M. Thirumaran
    R. Padmanaban
    Vijender Kumar Solanki
    Peer-to-Peer Networking and Applications, 2020, 13 : 1152 - 1175
  • [9] Incremental clustering of mixed data based on distance hierarchy
    Hsu, Chung-Chian
    Huang, Yan-Ping
    EXPERT SYSTEMS WITH APPLICATIONS, 2008, 35 (03) : 1177 - 1185
  • [10] An Artificial Immune Based Incremental Data Clustering Algorithm
    Xiao, Xin
    ADVANCES IN CIVIL ENGINEERING II, PTS 1-4, 2013, 256-259 : 2935 - 2938