Exploratory clustering and visualization

被引：4
|
作者：
Nowak-Brzezinska, Agnieszka [1 ]
Xieski, Tomasz [1 ]
机构：
[1] Univ Silesia, Inst Comp Sci, PL-41200 Sosnowiec, Poland
来源：
KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS 18TH ANNUAL CONFERENCE, KES-2014 | 2014年 / 35卷
关键词：
clustering; DBSCAN; AHC; cluster visualization; Squarified Treemaps;
D O I：
10.1016/j.procs.2014.08.196
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this work the topic of applying clustering as a knowledge extraction method from real-world data is discussed. Authors propose a two-phase cluster creation and visualization technique, which combines hierarchical and density-based algorithms(1). What is more, authors analyze the impact of data sampling on the result of searching through such a structure. Particular attention was also given to the problem of cluster visualization. Authors review selected, two-dimensional approaches, stating their advantages and drawbacks in the context of representing complex cluster structures. (C) 2014 Published by Elsevier B.V.
引用
收藏
页码：1082 / 1091
页数：10
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