DYNAMIC INTERACTION GRAPHS WITH PROBABILISTIC EDGE DECAY

    公开(公告)号:US20180232916A1

    公开(公告)日:2018-08-16

    申请号:US15951064

    申请日:2018-04-11

    CPC classification number: G06T11/206 G06K9/6296

    Abstract: A computer-implemented method, according to one embodiment, includes: generating two or more sample graphs by sampling edges of a current snapshot of a dynamic graph, generating two or more partial results by executing an algorithm on the two or more sample graphs, combining the partial results into a final result, and incrementally maintaining the sample graphs. Edges included in the current snapshot of a dynamic graph and which were added to the dynamic graph in a most recent update thereto are included in each of the generated two or more sample graphs. Moreover, incrementally maintaining the sample graphs includes: subsampling each of the edges of each of the sample graphs at a given time by applying a Bernoulli trial, and combining a result of the subsampling with new edges received in a batch corresponding to the given time to form new sample graphs.

    Dynamic interaction graphs with probabilistic edge decay

    公开(公告)号:US10249070B2

    公开(公告)日:2019-04-02

    申请号:US15951064

    申请日:2018-04-11

    Abstract: A computer-implemented method, according to one embodiment, includes: generating two or more sample graphs by sampling edges of a current snapshot of a dynamic graph, generating two or more partial results by executing an algorithm on the two or more sample graphs, combining the partial results into a final result, and incrementally maintaining the sample graphs. Edges included in the current snapshot of a dynamic graph and which were added to the dynamic graph in a most recent update thereto are included in each of the generated two or more sample graphs. Moreover, incrementally maintaining the sample graphs includes: subsampling each of the edges of each of the sample graphs at a given time by applying a Bernoulli trial, and combining a result of the subsampling with new edges received in a batch corresponding to the given time to form new sample graphs.

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