Improving Co-Clustering Efficiency for Hetrogenous Fusion in Multimedia Data

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Provided by: The International Journal of Innovative Research in Computer and Communication Engineering
Topic: Enterprise Software
Format: PDF
In order to retrieve information or web document, it is required to manage or scale very large repositories in order to get the information of demand. So clustering techniques are employed in order to enhance searching. An efficient co-clustering algorithm GHF-ART is used here (Generalized form of Heterogeneous Fusion Adaptive Resonance Theory). The main advantages of this technique are that it uses a multiple channel and each channel is feed with different data pattern so that efficiency increases. The main advantages of this algorithm are that it have strong noise resistance, channel weighting factors are adaptive, low computational overhead and clustering technique are incremental.
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