Finding Community Structure of Bayesian Networks by Improved K-means Algorithm

被引：0
|
作者：
Wang Manxi [1 ]
Wang Liandong [1 ]
Wang Chenfeng [2 ]
Gao Xiaoguang [2 ]
Di Ruohai [2 ]
机构：
[1] State Key Lab Complex Electromagnet Environm Effe, Luoyang, Henan, Peoples R China
[2] Northwestern Polytech Univ, Xian, Shanxi, Peoples R China
来源：
2018 IEEE 3RD INTERNATIONAL CONFERENCE ON IMAGE, VISION AND COMPUTING (ICIVC) | 2018年
关键词：
Bayesian network; community structure; improved K-means algorithm;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Many Bayesian networks display community structure; study community structure helps to reduce the complexity of learning Bayesian network in high-dimensional data. To find the community structure of Bayesian networks, this paper proposes an improved K-means algorithm by incorporating the mutual information into the K-means algorithm and modifying the iteration conditions. Experiments show that the proposed algorithm is suitable for block tasks of Bayesian network. Compared with FastNewman algorithm, the proposed algorithm can obtain accurate results in a shorter time.
引用
收藏
页码：865 / 869
页数：5
相关论文
共 50 条
  • [41] Improved MapReduce k-Means Clustering Algorithm with Combiner
    Anchalia, Prajesh P.
    2014 UKSIM-AMSS 16TH INTERNATIONAL CONFERENCE ON COMPUTER MODELLING AND SIMULATION (UKSIM), 2014, : 386 - 391
  • [42] Improved Document Clustering using K-means Algorithm
    Bide, Pramod
    Shedge, Rajashree
    2015 IEEE INTERNATIONAL CONFERENCE ON ELECTRICAL, COMPUTER AND COMMUNICATION TECHNOLOGIES, 2015,
  • [43] Tobacco Distribution Based on Improved K-means Algorithm
    Zheng, Bin
    Tang, Fa-zhe
    Yang, Hua-long
    PROCEEDINGS OF 2009 IEEE INTERNATIONAL CONFERENCE ON SERVICE OPERATION, LOGISTICS AND INFORMATICS, 2009, : 724 - +
  • [44] Improved K-means Algorithm in User Behavior Analysis
    Xue, Liming
    Luan, Weixin
    2015 NINTH INTERNATIONAL CONFERENCE ON FRONTIER OF COMPUTER SCIENCE AND TECHNOLOGY FCST 2015, 2015, : 338 - 341
  • [45] An Improved K-Means Algorithm Based on Evidence Distance
    Zhu, Ailin
    Hua, Zexi
    Shi, Yu
    Tang, Yongchuan
    Miao, Lingwei
    ENTROPY, 2021, 23 (11)
  • [46] An Improved Genetic K-Means Algorithm for Spatial Clustering
    Wang, Yuanni
    Ge, Fei
    PROGRESS IN INTELLIGENCE COMPUTATION AND APPLICATIONS, 2008, : 123 - 126
  • [47] An Improved K-Means Algorithm Based on Contour Similarity
    Zhao, Jing
    Bao, Yanke
    Li, Dongsheng
    Guan, Xinguo
    MATHEMATICS, 2024, 12 (14)
  • [48] An Improved K-means Algorithm based on Mapreduce and Grid
    Ma, Li
    Gu, Lei
    Li, Bo
    Ma, Yue
    Wang, Jin
    INTERNATIONAL JOURNAL OF GRID AND DISTRIBUTED COMPUTING, 2015, 8 (01): : 189 - 199
  • [49] Improved K-means clustering algorithm in intrusion detection
    Xiao, ShiSong
    Li, XiaoXu
    Liu, XueJiao
    2008 PROCEEDINGS OF INFORMATION TECHNOLOGY AND ENVIRONMENTAL SYSTEM SCIENCES: ITESS 2008, VOL 2, 2008, : 771 - 775
  • [50] Improved K-Means algorithm in text semantic clustering
    Ma, Junhong
    Open Cybernetics and Systemics Journal, 2014, 8 : 530 - 534
12345