IJBTT

Hierarchical Clustering in Temporal Databases

	International Journal of Recent Engineering Science (IJRES)
	© 2014 by IJRES Journal
	Volume-1 Issue-1
	Year of Publication : 2014
	Authors : Dr.G.Sreesharma
	DOI : 10.14445/23497157/IJRES-V1I1P104

How to Cite?

Dr.G.Sreesharma, "Hierarchical Clustering in Temporal Databases," International Journal of Recent Engineering Science, vol. 1, no. 1, pp. 17-23, 2014. Crossref, https://doi.org/10.14445/23497157/IJRES-V1I1P104

Abstract
This project report discusses about the design and implementation of an incremental system for clustering the data stream that are present in time series databases. The Online Divisive-Agglomerative Clustering system implemented in this project work continuously maintains a tree-like hierarchy of clusters that evolves with data, using a top-down strategy. Using correlation-based dissimilarity measure, each node is split by the farthest pair of streams. This system uses a merge operator which re-aggregates a previously split node, in order to react to changes in the correlation structure between time series. The split and merge operators act in response to changes in the diameters of existing clusters. Expanding the structure in this way leads to a decrease in the diameters of the clusters. This system has been designed to process thousands of data streams that flow at high rate. The main advantage of this system is the reduction in update time and memory usage. This system has been implemented using Java language in Windows Platform.

Keywords
Hierarchical Clustering, Database and System

Reference
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