A Method of Two-Stage Clustering with Constraints Using Agglomerative Hierarchical Algorithm and One-Pass k-Means plus

被引：5
|
作者：
Tamura, Yusuke [1 ]
Obara, Nobuhiro [1 ]
Miyamoto, Sadaaki [2 ]
机构：
[1] Univ Tsukuba, Masters Program Risk Engn, Tsukuba, Ibaraki 3058573, Japan
[2] Univ Tsukuba, Dept Risk Engn, Tsukuba, Ibaraki 3058573, Japan
来源：
KNOWLEDGE AND SYSTEMS ENGINEERING (KSE 2013), VOL 2 | 2014年 / 245卷
关键词：
D O I：
10.1007/978-3-319-02821-7_3
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The aim of this paper is to propose a two-stage method of clustering in which the first stage uses one-pass k-means++ and the second stage uses an agglomerative hierarchical algorithm. This method outperforms a foregoing two-stage algorithm by replacing the ordinary one-pass k-means by one-pass k-means++ in the first stage. Pairwise constraints are also taken into consideration in order to improve its performance. Effectiveness of the proposed method is shown by numerical examples.
引用
收藏
页码：9 / 19
页数：11
相关论文
共 50 条
  • [1] A Method of Two-Stage Clustering with Constraints Using Agglomerative Hierarchical Algorithm and One-Pass K-Means
    Obara, Nobuhiro
    Miyamoto, Sadaaki
    6TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS, AND THE 13TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS, 2012, : 1540 - 1544
  • [2] A Method of Two Stage Clustering Using Agglomerative Hierarchical Algorithms with One-Pass k-Means plus plus or k-Median plus
    Tamura, Yusuke
    Miyamoto, Sadaaki
    2014 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING (GRC), 2014, : 281 - 285
  • [3] Two-Stage Clustering Using One-Pass K-Medoids and Medoid-Based Agglomerative Hierarchical Algorithms
    Tamura, Yusuke
    Miyamoto, Sadaaki
    2014 JOINT 7TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS (SCIS) AND 15TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS (ISIS), 2014, : 484 - 488
  • [4] Two-Stage Clustering with k-Means Algorithm
    Salman, Raied
    Kecman, Vojislav
    Li, Qi
    Strack, Robert
    Test, Erick
    RECENT TRENDS IN WIRELESS AND MOBILE NETWORKS, 2011, 162 : 110 - 122
  • [5] Two-stage clustering and routing problem by using FCM and K-means with genetic algorithm
    Pekel Ozmen, Ebru
    Kucukdeniz, Tarik
    SIGMA JOURNAL OF ENGINEERING AND NATURAL SCIENCES-SIGMA MUHENDISLIK VE FEN BILIMLERI DERGISI, 2024, 42 (04): : 1030 - 1038
  • [6] A Two-Stage Clustering Algorithm based on Improved K-means and Density Peak Clustering
    Xiao, Na
    Zhou, Xu
    Huang, Xin
    Yang, Zhibang
    2019 10TH IEEE INTERNATIONAL CONFERENCE ON BIG KNOWLEDGE (ICBK 2019), 2019, : 296 - 301
  • [7] An improved Agglomerative levels K-means clustering algorithm
    Yu Jiankun
    Guo Jun
    2014 INTERNATIONAL CONFERENCE ON MANAGEMENT OF E-COMMERCE AND E-GOVERNMENT (ICMECG), 2014, : 221 - 224
  • [8] Using k-Means plus plus Algorithm for Researchers Clustering
    Rukmi, Alvida Mustika
    Iqbal, Ikhwan Muhammad
    INTERNATIONAL CONFERENCE ON MATHEMATICS: PURE, APPLIED AND COMPUTATION: EMPOWERING ENGINEERING USING MATHEMATICS, 2017, 1867
  • [9] A two-stage clustering method combining ant colony SOM and K-means
    Department of Industrial Engineering and Management Information, Huafan University, Taipei County, 223, Taiwan
    不详
    J. Inf. Sci. Eng., 2008, 5 (1445-1460):
  • [10] A two-stage clustering method combining ant colony SOM and K-means
    Chi, Sheng-Chai
    Yang, Chih-Chieh
    JOURNAL OF INFORMATION SCIENCE AND ENGINEERING, 2008, 24 (05) : 1445 - 1460
12345