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    • 7. 发明申请
    • Ranking Related Objects Using Blink Model Based Relation Strength Determinations
    • 使用基于眨眼模型的关系强度确定来排列相关对象
    • US20170011037A1
    • 2017-01-12
    • US14791789
    • 2015-07-06
    • International Business Machines Corporation
    • Haifeng QianHui Wan
    • G06F17/30
    • G06F17/30867G06F17/30958G06Q50/01
    • Mechanisms are provided for performing a cognitive operation. An input graph is received having a plurality of first nodes, where subsets of first nodes are coupled to one another via first edges and each first edge has an associated weight. A blinking graph model is generated based on the graph, where blink rates are associated with second edges and are calculated based on weights of corresponding first edges in the input graph. The blink rate specifies a fraction of time a corresponding second edge is determined to be present in the blinking graph model. A relatedness metric is calculated for a target node relative to a node of interest based on the blink rates of the second edges. The relatedness metric indicates a degree of relatedness of the target node to the node of interest. A cognitive operation is then performed based on the relatedness metric.
    • 提供了进行认知手术的机制。 接收具有多个第一节点的输入图,其中第一节点的子集经由第一边缘彼此耦合,并且每个第一边缘具有相关联的权重。 基于图形生成闪烁图形模型,其中闪烁速率与第二边缘相关联,并且基于输入图中对应的第一边缘的权重来计算。 闪烁速率指定相应的第二个边沿被确定为存在于闪烁图形模型中的一小段时间。 基于第二边缘的闪烁速率,针对目标节点相对于感兴趣的节点计算相关性度量。 相关性度量指示目标节点与感兴趣的节点的相关程度。 然后基于相关性度量执行认知操作。