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    • 7. 发明申请
    • PARALLEL METHOD FOR AGGLOMERATIVE CLUSTERING OF NON-STATIONARY DATA
    • 用于非静态数据的并行聚类的并行方法
    • US20140359626A1
    • 2014-12-04
    • US13906169
    • 2013-05-30
    • Qualcomm Incorporated
    • Isaac David GuedaliaSarah Glickfield
    • G06F9/46
    • G06F9/466G06F9/54G06N5/043G06N99/005
    • The disclosure is directed to clustering a stream of data points. An aspect receives the stream of data points, determines a plurality of cluster centroids, divides the plurality of cluster centroids among a plurality of threads and/or processors, assigns a portion of the stream of data points to each of the plurality of threads and/or processors, and combines a plurality of clusters generated by the plurality of threads and/or processors to generate a global universe of clusters. An aspect assigns a portion of the stream of data points to each of a plurality of threads and/or processors, wherein each of the plurality of threads and/or processors determines one or more cluster centroids and generates one or more clusters around the one or more cluster centroids, and combines the one or more clusters from each of the plurality of threads and/or processors to generate a global universe of clusters.
    • 本公开旨在对数据点流进行聚类。 方面接收数据点流,确定多个聚类质心,在多个线程和/或处理器之间划分多个聚类质心,将数据流流的一部分分配给多个线程中的每一个和/ 或处理器,并且组合由所述多个线程和/或处理器生成的多个集群以生成集群的全局宇宙。 方面将数据流流的一部分分配给多个线程和/或处理器中的每一个,其中多个线程和/或处理器中的每个线程和/或处理器确定一个或多个集群质心并且围绕该一个或多个处理器生成一个或多个集群 更多的集群中心,并且组合来自多个线程和/或处理器中的每一个的一个或多个集群以生成集群的全局Universe。
    • 10. 发明授权
    • Parallel method for agglomerative clustering of non-stationary data
    • 非平稳数据聚类聚类的并行方法
    • US09411632B2
    • 2016-08-09
    • US13906169
    • 2013-05-30
    • Qualcomm Incorporated
    • Isaac David GuedaliaSarah Glickfield
    • G06F9/46G06F15/173G06F9/54G06N5/04G06N99/00
    • G06F9/466G06F9/54G06N5/043G06N99/005
    • The disclosure is directed to clustering a stream of data points. An aspect receives the stream of data points, determines a plurality of cluster centroids, divides the plurality of cluster centroids among a plurality of threads and/or processors, assigns a portion of the stream of data points to each of the plurality of threads and/or processors, and combines a plurality of clusters generated by the plurality of threads and/or processors to generate a global universe of clusters. An aspect assigns a portion of the stream of data points to each of a plurality of threads and/or processors, wherein each of the plurality of threads and/or processors determines one or more cluster centroids and generates one or more clusters around the one or more cluster centroids, and combines the one or more clusters from each of the plurality of threads and/or processors to generate a global universe of clusters.
    • 本公开旨在对数据点流进行聚类。 方面接收数据点流,确定多个聚类质心,在多个线程和/或处理器之间划分多个聚类质心,将数据流流的一部分分配给多个线程中的每一个和/ 或处理器,并且组合由所述多个线程和/或处理器生成的多个集群以生成集群的全局宇宙。 方面将数据流流的一部分分配给多个线程和/或处理器中的每一个,其中多个线程和/或处理器中的每个线程和/或处理器确定一个或多个集群质心并且围绕该一个或多个处理器生成一个或多个集群 更多的集群中心,并且组合来自多个线程和/或处理器中的每一个的一个或多个集群以生成集群的全局Universe。