Abstract
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.
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Rajendra Prasad, K., Eswara Reddy, B. (2016). Context-Aware Graph-Based Visualized Clustering Approach (CAVCA). In: Chaki, R., Cortesi, A., Saeed, K., Chaki, N. (eds) Advanced Computing and Systems for Security. Advances in Intelligent Systems and Computing, vol 395. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2650-5_16
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DOI: https://doi.org/10.1007/978-81-322-2650-5_16
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