文章基本信息

标题：Improving Co-Clustering Efficiency for Hetrogenous Fusion in Multimedia Data
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作者：Aparna A P ; Neethu Susan Jacob
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2015
卷号：3
期号：6
DOI：10.15680/ijircce.2015.0306156
出版社：S&S Publications
摘要：In order to retrieve information or web document, it is required to manage or scale very largerepositories in order to get the information of demand. So clustering techniques are employed in order to enhancesearching.. An efficient co-clustering algorithm GHF-ART is used here (Generalized form of Heterogeneous FusionAdaptive resonance Theory). The main advantages of this technique are that it uses a multiple channel and eachchannel is feed with different data pattern so that efficiency increases. The main advantages of this algorithm are that ithave strong noise resistance, channel weighting factors are adaptive, low computational overhead and clusteringtechnique are incremental. Since it has a lot of advantage, this mechanism yet has certain drawbacks. A novel algorithmknown as sparse graph based discriminant analysis block-structured similarity matrix can be used for feature selectionwhich effectively selects the feature from a large set of dataset. That means this algorithm can be used fordimensionality reduction.
关键词：10.15680/ijircce.2015.0306156