Search Results - (( its application customization algorithm ) OR ( _ application clustering algorithm ))*

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    Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream by Abdulateef, Alaa Fareed

    Published 2023
    “…The AGMB algorithm is built upon three algorithms: 1) Grid-Multi-Buffer Stream Clustering (GMBSC), 2) Cautious Grid-Multi-Buffer Stream Clustering (C-GMBSC) and 3) Adaptive-Grid-Multi-Buffer Stream Clustering (A-GMBSC). …”
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    Thesis
  2. 2

    Social networks content analysis for peacebuilding application by Shaikh, Muniba, Salleh, Norsaremah, Abdullah, Lili Marziana

    Published 2015
    “…Moreover, the research proposes to use lexical analysis (LA) method to extract the SNs features, 1st order context representation (CR) technique to represent the context of the extracted features, DBSCAN clustering algorithm for data management by making different clusters, ranking algorithm, Log likelihood ratio and SVM techniques for content analysis and classification. …”
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    Proceeding Paper
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    Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation by Alia, Osama Moh’d Radi

    Published 2011
    “…However, two main issues plague these clustering algorithms: initialization sensitivity of cluster centers and unknown number of actual clusters in the given dataset. …”
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    Thesis
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    On density-based data streams clustering algorithms: A survey by Teh, Y.W.

    Published 2017
    “…Recently, a lot of density-based clustering algorithms are extended for data streams. …”
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    Conference or Workshop Item
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    Fuzzy clustering algorithms and their applications to chemical datasets by Shah, Jehan Zeb, Salim, Naomie

    Published 2005
    “…In this work the importance of fuzzy based clustering methods is highlighted and their applications in the field of chemoinformatics, and issues involved are reviewed. …”
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    Conference or Workshop Item
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    An adaptive density-based method for clustering evolving data streams / Amineh Amini by Amini, Amineh

    Published 2014
    “…Due to these characteristics the traditional densitybased clustering is not applicable. Recently, a number of density-based algorithms have been developed for clustering data streams. …”
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    Thesis
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    Cluster Analysis of Data Points using Partitioning and Probabilistic Model-based Algorithms by Raheem, Ajiboye Adeleke, Hauwau, Isah-Kebbe, O., Oladele Tinuke

    Published 2014
    “…Exploring the dataset features through the application of clustering algorithms is a viable means by which the conceptual description of such data can be revealed for better understanding, grouping and decision making. …”
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    Article
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