CLUSTER ANALYSIS - DATA MINING TECHNIQUE FOR DISCOVERING NATURAL GROUPINGS IN THE DATA

被引:2
|
作者
Pastuchova, Elena [1 ]
Vaclavikova, Stefania [2 ]
机构
[1] Slovak Univ Technol Bratislava, Dept Math, Inst Informat & Math, Fac Elect Engn & Informat Technol, Bratislava, Slovakia
[2] Slovak Univ Technol Bratislava, Dept Math & Descript Geometry, Fac Civil Engn, Bratislava, Slovakia
关键词
data mining; clustering; K-means; self organizing maps; density based algorithm;
D O I
10.2478/jee-2013-0019
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Amount of data stored in databases has been growing rapidly. With the technology of pattern recognition and statistical and mathematical techniques sieved across the stored information, data mining helps researchers recognize important facts, relationships, trends, patterns, derogations and anomalies that might otherwise go undetected. One of the major data mining techniques is clustering In this paper some of clustering methods, helpful in many applications, are compared. We assess the suitability of the software that we used for clustering.
引用
收藏
页码:128 / 131
页数:4
相关论文
共 50 条
  • [31] Application of fuzzy cluster analysis for medical image data mining
    Wang, Shuyan
    Zhou, Mingquan
    Geng, Guohua
    [J]. 2005 IEEE International Conference on Mechatronics and Automations, Vols 1-4, Conference Proceedings, 2005, : 631 - 636
  • [32] Finding the natural groupings in a data set using genetic algorithms
    Chowdhury, N
    Jana, P
    [J]. APPLIED COMPUTING, PROCEEDINGS, 2004, 3285 : 26 - 33
  • [33] Mining the Web: Discovering knowledge from hypertext data
    Jansen, BJ
    [J]. INFORMATION PROCESSING & MANAGEMENT, 2006, 42 (01) : 317 - 318
  • [34] A data mining approach to discovering reliable sequential patterns
    Shyur, Huan-Jyh
    Jou, Chichang
    Chang, Keng
    [J]. JOURNAL OF SYSTEMS AND SOFTWARE, 2013, 86 (08) : 2196 - 2203
  • [35] NCDS: data mining for discovering interesting network characteristics
    Zaki, M
    Sobh, TS
    [J]. INFORMATION AND SOFTWARE TECHNOLOGY, 2005, 47 (03) : 189 - 198
  • [36] Discovering the Drivers of Football Match Outcomes with Data Mining
    Carpita, Maurizio
    Sandri, Marco
    Simonetto, Anna
    Zuccolotto, Paola
    [J]. QUALITY TECHNOLOGY AND QUANTITATIVE MANAGEMENT, 2015, 12 (04): : 561 - 577
  • [37] Discovering the City by Mining Diverse and Multimodal Data Streams
    Kuo, Yin-Hsi
    Chen, Yan-Ying
    Chen, Bor-Chun
    Lee, Wen-Yu
    Wu, Chun-Che
    Lin, Chia-Hung
    Hou, Yu-Lin
    Cheng, Wen-Feng
    Tsai, Yi-Chih
    Hung, Chung-Yen
    Hsieh, Liang-Chi
    Hsu, Winston
    [J]. PROCEEDINGS OF THE 2014 ACM CONFERENCE ON MULTIMEDIA (MM'14), 2014, : 201 - 204
  • [38] Combined Mining: Discovering Informative Knowledge in Complex Data
    Cao, Longbing
    Zhang, Huaifeng
    Zhao, Yanchang
    Luo, Dan
    Zhang, Chengqi
    [J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2011, 41 (03): : 699 - 712
  • [39] Mining the Web: Discovering knowledge from hypertext data
    Srisa-ard, S
    [J]. ONLINE INFORMATION REVIEW, 2003, 27 (04) : 291 - 291
  • [40] Mining the Web: Discovering knowledge from hypertext data
    Krishnamurthy, S
    [J]. JOURNAL OF MARKETING RESEARCH, 2005, 42 (03) : 380 - 382