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

页码：247 / 260

页数：14

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