An Incremental Shared Nearest Neighbour Clustering Approach for Numerical Data Using an Efficient Distance Measure

Provided by: International Journal Of Engineering And Computer Science
Topic: Big Data
Format: PDF
Clustering is one of the prominent fields of data mining. A major drawback of traditional clustering algorithms is that they perform clustering on static databases. But in real time databases are dynamic. Therefore incremental clustering algorithms have become an interesting area of research wherein clustering is performed on the incremental data without having to cluster the entire data from scrape. In this paper, a new incremental clustering algorithm called Incremental Shared Nearest Neighbor Clustering Approach (ISNNCA) for numeric data has been proposed.

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