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Pipelined incremental clustering algorithm

机译:流水线增量聚类算法

摘要

Systems and methods are provided for large-scale, incrementing clustering. A plurality of processing nodes each include a processor and a non-transitory computer readable medium. The non-transitory computer readable medium stores a plurality of clusters of feature vectors and machine executable instructions for determining a plurality of values for a distance metric relating each of the plurality of clusters to an input feature vector and selecting a cluster having a best value for the distance metric. An arbitrator is configured to receive the selected cluster and best value for the distance metric from each of the plurality of processing nodes and determine a winning cluster as one of the selected clusters and a new cluster. A multiplexer is configured to receive the winning cluster and provide the winning cluster and a new input feature vector to each of the plurality of processing nodes.
机译:提供了用于大规模增量聚类的系统和方法。多个处理节点各自包括处理器和非暂时性计算机可读介质。非暂时性计算机可读介质存储特征向量的多个集群和机器可执行指令,该机器可执行指令用于确定将多个集群中的每个集群与输入特征向量相关联的距离度量的多个值,并选择具有最佳值的集群。距离度量。仲裁器被配置为从多个处理节点中的每一个接收所选集群和距离度量的最佳值,并将获胜集群确定为所选集群和新集群之一。多路复用器被配置为接收获胜集群并且将获胜集群和新的输入特征向量提供给多个处理节点中的每一个。

著录项

  • 公开/公告号US8930422B2

    专利类型

  • 公开/公告日2015-01-06

    原文格式PDF

  • 申请/专利权人 MICHAEL D. BLACK;

    申请/专利号US201213487838

  • 发明设计人 MICHAEL D. BLACK;

    申请日2012-06-04

  • 分类号G06F7/00;

  • 国家 US

  • 入库时间 2022-08-21 15:16:35

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