Context-Aware Graph-Based Visualized Clustering Approach (CAVCA)

被引:0
|
作者
Prasad, K. Rajendra [1 ]
Reddy, B. Eswara [2 ]
机构
[1] Rajeev Gandhi Mem Coll Engn & Technol, Dept IT, Nandyal, AP, India
[2] JNTUA Coll Engn, Dept CSE, Ananthapuramu, AP, India
来源
ADVANCED COMPUTING AND SYSTEMS FOR SECURITY, VOL 1 | 2016年 / 395卷
关键词
Clustering; VAT; Clustering tendency; Hypergraph; TENDENCY;
D O I
10.1007/978-81-322-2650-5_16
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The Clustering algorithms cannot detect the number of clusters for unlabeled data. The visual access tendency (VAT) is recognized as the best approach for cluster detection. However, context-aware-based graphs (CAG) give more informative cluster assessment for VAT. Hence, we extend the VAT using CAG, known as CAVAT. This paper investigates the existing cluster detection methods and proposes a data clustering method for the CAVAT for archiving the efficient clustering results.
引用
收藏
页码:247 / 260
页数:14
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