<bold>Clustering Categorical Data using Silhouette Coefficient as a Relocating Measure</bold>

被引：0
|
作者：
Aranganayagi, S. [1 ]
Thangavel, K. [2 ]
机构：
[1] JKK Nataraja Coll Arts & Sci, Komarapalayam 638183, Tamil Nadu, India
[2] Periyar Univ, Dept Comp Sci, Salem 636011, Tamil Nadu, India
来源：
ICCIMA 2007: INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND MULTIMEDIA APPLICATIONS, VOL III, PROCEEDINGS | 2007年
关键词：
data mining; clustering; categorical data; silhouette coefficient;
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：
Cluster analysis is an unsupervised learning method that constitutes a cornerstone of an intelligent data analysis process. Clustering categorical data is an important research area data mining. In this paper we propose a novel algorithm to cluster categorical data. Based on the minimum dissimilarity value objects are grouped into cluster. In the merging process, the objects are relocated using silhouette coefficient. Experimental results show that the proposed method is efficient.
引用
收藏
页码：13 / +
页数：3
相关论文
共 50 条
  • [31] Fuzzy clustering of categorical data using fuzzy centroids
    Kim, DW
    Lee, KH
    Lee, D
    PATTERN RECOGNITION LETTERS, 2004, 25 (11) : 1263 - 1271
  • [32] Clustering Categorical Data Using Rough Membership Function
    Kumar, B. Suresh
    Reddy, H. Venkateswara
    Raju, T. Ankamma
    Vennam, Preethi
    2014 6TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMMUNICATION NETWORKS, 2014, : 602 - 607
  • [33] COIN: Correlation Index-Based Similarity Measure for Clustering Categorical Data
    Sowmiya, N.
    Gupta, N. Srinivasa
    Natarajan, Elango
    Valarmathi, B.
    Elamvazuthi, I.
    Parasuraman, S.
    Kit, Chun Ang
    Freitas, Lidio Inacio
    Abraham Gnanamuthu, Ezra Morris
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2022, 2022
  • [34] Categorical data visualization and clustering using subjective factors
    Chang, CH
    Ding, ZK
    DATA & KNOWLEDGE ENGINEERING, 2005, 53 (03) : 243 - 262
  • [35] Categorical data visualization and clustering using subjective factors
    Chang, CH
    Ding, ZK
    DATA WAREHOUSING AND KNOWLEDGE DISCOVERY, PROCEEDINGS, 2004, 3181 : 229 - 238
  • [36] Driving Innovation Using Big Open Linked Data (BOLD) Panel
    Dwivedi, Yogesh K.
    Weerakkody, Vishanth
    Janssen, Marijn
    Millard, Jeremy
    Hidders, Jan
    Snijders, Dhoya
    Rana, Nripendra P.
    Slade, Emma L.
    OPEN AND BIG DATA MANAGEMENT AND INNOVATION, I3E 2015, 2015, 9373 : 3 - 9
  • [37] Using the Silhouette Coefficient for Representative Search of Team Tactics in Noisy Data
    Schwenkreis, Friedemann
    PROCEEDINGS OF THE 11TH INTERNATIONAL CONFERENCE ON DATA SCIENCE, TECHNOLOGY AND APPLICATIONS (DATA), 2022, : 193 - 202
  • [38] COIN: Correlation Index-Based Similarity Measure for Clustering Categorical Data
    Sowmiya, N.
    Gupta, N.Srinivasa
    Natarajan, Elango
    Valarmathi, B.
    Elamvazuthi, I.
    Parasuraman, S.
    Kit, Chun Ang
    Freitas, Lídio Inácio
    Abraham Gnanamuthu, Ezra Morris
    Mathematical Problems in Engineering, 2022, 2022
  • [39] Driving public sector innovation using big and open linked data (BOLD)
    Marijn Janssen
    David Konopnicki
    Jane L. Snowdon
    Adegboyega Ojo
    Information Systems Frontiers, 2017, 19 : 189 - 195
  • [40] Study protocol: The back pain outcomes using longitudinal data (BOLD) registry
    Jarvik, Jeffrey G.
    Comstock, Bryan A.
    Bresnahan, Brian W.
    Nedeljkovic, Srdjan S.
    Nerenz, David R.
    Bauer, Zoya
    Avins, Andrew L.
    James, Kathryn
    Turner, Judith A.
    Heagerty, Patrick
    Kessler, Larry
    Friedly, Janna L.
    Sullivan, Sean D.
    Deyo, Richard A.
    BMC MUSCULOSKELETAL DISORDERS, 2012, 13 : 64
12345