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

页码：1082 / 1091

页数：10

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