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IDEAS
2006
IEEE

PBIRCH: A Scalable Parallel Clustering algorithm for Incremental Data

14 years 5 months ago
PBIRCH: A Scalable Parallel Clustering algorithm for Incremental Data
We present a parallel version of BIRCH with the objective of enhancing the scalability without compromising on the quality of clustering. The incoming data is distributed in a cyclic manner (or block cyclic manner if the data is bursty) to balance the load among processors. The algorithm is implemented on a message passing share-nothing model. Experiments show that for very large data sets the algorithm scales nearly linearly with the increasing number of processors. Experiments also show that clusters obtained by PBIRCH are comparable to those obtained using BIRCH.
Ashwani Garg, Ashish Mangla, Neelima Gupta, Vasudh
Added 11 Jun 2010
Updated 11 Jun 2010
Type Conference
Year 2006
Where IDEAS
Authors Ashwani Garg, Ashish Mangla, Neelima Gupta, Vasudha Bhatnagar
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