The accumulating nature of the data makes the datasets intractably huge over time. In this case, an incremental solution relieves the issue because it partitions the problem. We propose an incremental version of our algorithm of hierarchical co-clustering. It starts from an intermediate solution computed on the previous version of the data and it updates the co-clustering results considering only the added block of data. This solution has the merit of speeding up the computation with respect to the original approach that would recompute the result on the overall dataset. In addition, the incremental algorithm guarantees approximately the same answer than the original version, but it saves much computational load.

iHiCC: Incremental Flat and Hierarchical Co-Clustering

IENCO, Dino;PENSA, Ruggero Gaetano;MEO, Rosa
2012

Abstract

The accumulating nature of the data makes the datasets intractably huge over time. In this case, an incremental solution relieves the issue because it partitions the problem. We propose an incremental version of our algorithm of hierarchical co-clustering. It starts from an intermediate solution computed on the previous version of the data and it updates the co-clustering results considering only the added block of data. This solution has the merit of speeding up the computation with respect to the original approach that would recompute the result on the overall dataset. In addition, the incremental algorithm guarantees approximately the same answer than the original version, but it saves much computational load.
0.9
DIPARTIMENTO DI INFORMATICA, Università di Torino
http://www.di.unito.it/~pensa/software.html
Incremental clustering; co-clustering; Hierarchical Clustering
D. Ienco; R.G Pensa; R. Meo
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2318/127009
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