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    Executing graph path queries
    3.
    发明授权
    Executing graph path queries 有权

    公开(公告)号：US10176220B2

    公开(公告)日：2019-01-08

    申请号：US14967684

    申请日：2015-12-14

    Applicant: International Business Machines Corporation

    Inventor： Mir Hamid Pirahesh ,  Yuanyuan Tian

    IPC: G06F17/30

    Abstract: Embodiments of the invention relate to executing graph path queries. A database stores data entities and attributes in node tables and stores links between nodes in an edge table. Edges form a path between a source node and a target node. A source node set is generated and joined with the edge table to produce a first intermediate set. Similarly, a target node set is generated and joined with the edge table to produce a second intermediate set. A result path is generated through a joining of the first and second intermediate paths and application of a length condition.

    SUBGRAPH-BASED DISTRIBUTED GRAPH PROCESSING
    5.
    发明申请
    SUBGRAPH-BASED DISTRIBUTED GRAPH PROCESSING 有权
    基于分类的分布图处理

    公开(公告)号：US20150170316A1

    公开(公告)日：2015-06-18

    申请号：US14108812

    申请日：2013-12-17

    Applicant: International Business Machines Corporation

    Inventor： Andrey Balmin ,  Severin A. Corsten ,  John A. McPherson, JR. ,  Shirish Tatikonda ,  Yuanyuan Tian

    IPC: G06T1/20

    CPC classification number: G06F17/10 ,  G06F17/30958 ,  G06F17/509

    Abstract: Embodiments relate to subgraph-based distributed graph processing. An aspect includes receiving an input graph comprising a plurality of vertices. Another aspect includes partitioning the input graph into a plurality of subgraphs, each subgraph comprising internal vertices and boundary vertices. Another aspect includes assigning one or more respective subgraphs to each of a plurality of workers. Another aspect includes initiating processing of the plurality of subgraphs by performing a series of processing steps comprising: processing the internal vertices and boundary vertices internally within each of the subgraphs; detecting that a change was made to a boundary vertex of a first subgraph during the internal processing; and sending a message from a first worker to which the first subgraph is assigned to a second worker to which a second subgraph is assigned in response to detecting the change that was made to the boundary vertex of the first subgraph.

    Abstract translation: 实施例涉及基于子图的分布式图处理。 一方面包括接收包括多个顶点的输入图。 另一方面包括将输入图划分成多个子图，每个子图包括内部顶点和边界顶点。 另一方面包括将一个或多个相应子图分配给多个工人中的每一个。 另一方面包括通过执行一系列处理步骤来启动多个子图的处理，包括：在每个子图内部处理内部顶点和边界顶点; 检测在内部处理期间对第一子图的边界顶点的变化; 以及响应于检测到对所述第一子图的所述边界顶点所做的改变，将从所述第一子图分配给第一子图的消息发送到分配有第二子图的第二工作者。

    SPARSITY-DRIVEN MATRIX REPRESENTATION TO OPTIMIZE OPERATIONAL AND STORAGE EFFICIENCY
    6.
    发明申请
    SPARSITY-DRIVEN MATRIX REPRESENTATION TO OPTIMIZE OPERATIONAL AND STORAGE EFFICIENCY 有权
    分散驱动矩阵表示优化运行和存储效率

    公开(公告)号：US20150113031A1

    公开(公告)日：2015-04-23

    申请号：US14058338

    申请日：2013-10-21

    Applicant: International Business Machines Corporation

    Inventor： Berthold Reinwald ,  Shirish Tatikonda ,  Yuanyuan Tian

    IPC: G06F17/16

    CPC classification number: G06F12/0223 ,  G06F17/16 ,  G06F2212/251

    Abstract: Embodiments of the invention relate to sparsity-driven matrix representation. In one embodiment, a sparsity of a matrix is determined and the sparsity is compared to a threshold. Computer memory is allocated to store the matrix in a first data structure format based on the sparsity being greater than the threshold. Computer memory is allocated to store the matrix in a second data structure format based on the sparsity not being greater than the threshold

    Abstract translation: 本发明的实施例涉及稀疏性驱动的矩阵表示。 在一个实施例中，确定矩阵的稀疏度并将稀疏性与阈值进行比较。 分配计算机存储器以基于稀疏度大于阈值的第一数据结构格式存储矩阵。 分配计算机存储器以基于不大于阈值的稀疏度将第二数据结构格式存储在矩阵中

    DYNAMIC INTERACTION GRAPHS WITH PROBABILISTIC EDGE DECAY
    8.
    发明申请
    DYNAMIC INTERACTION GRAPHS WITH PROBABILISTIC EDGE DECAY 审中-公开

    公开(公告)号：US20180232916A1

    公开(公告)日：2018-08-16

    申请号：US15951064

    申请日：2018-04-11

    Applicant: International Business Machines Corporation

    Inventor： Andrey Balmin ,  Peter J. Haas ,  John Sismanis ,  Yuanyuan Tian ,  Wenlei Xie

    IPC: G06T11/20

    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.

    Identifying influencers for topics in social media
    9.
    发明授权
    Identifying influencers for topics in social media 有权

    公开(公告)号：US09864807B2

    公开(公告)日：2018-01-09

    申请号：US15186975

    申请日：2016-06-20

    Applicant: International Business Machines Corporation

    Inventor： Andrey L. Balmin ,  Bin Bi ,  John Sismanis ,  Yuanyuan Tian

    IPC: G06F7/00 ,  G06F17/30 ,  G06Q30/02 ,  G06Q50/00

    CPC classification number: G06F17/30867 ,  G06F17/30696 ,  G06F17/30864 ,  G06F17/3089 ,  G06Q30/0201 ,  G06Q50/01

    Abstract: A computer determines social media influencers in a specific topic by receiving a dataset of information associated with a website, the information including a first list of users of the website and a list of content that each user posts on the website, wherein each user is associated with other users from the first list of users. The computer determines initial values representing variables of the dataset of information on the website, wherein the variables include one or more topics for the list of content that each user from the first list of users posts on the website. The computer performs an iteration of Gibbs Sampling utilizing the initial values. The computer determines the one or more new values representing variables of the dataset represent a distribution of the one or more topics for the list of content that each user from the first list of users posts.

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