Online Clustering Of Multiple Data Streams
Journal Title: International Journal of Research in Computer and Communication Technology - Year 2013, Vol 2, Issue 7
Abstract
This paper presents an online Clustering of Data Stream Algorithm which can be used for on-line summarization of multiple data stream over fixed time length. A data stream is a large and continuously increasing sequence of data collected from various data generating applications or equipments. Applications which requires processing of huge amounts of data such as sensor data analysis and financial applications, datastream mining plays very important role. For such analysis, single-pass algorithms that require a very less amount of memory are needed. Clustering can be used to group data streams into homogeneous clusters. It computes the synopsis of multiple data streams in single pass. This synopsis representation can be used by data miners for learning data characteristics.
Authors and Affiliations
Yogita Dada Fatangare, Pramod Patil
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