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Dynamic Ranking Objects based on Time Varying Event Network

机译:基于时间变化的事件网络动态排序对象

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The traditional node-ranking algorithms just rank the nodes of one network by the aggregation function to the network and do not refer to the sequence of the network events. We propose TVNM with dynamic ranking objects, which is a framework for quantifying' the relationship between objects over time. And we also propose the modified PageRank algorithm based on TVNM. We compare the PageRank algorithm to the modified PageRank algorithm on a large organizational data set。
机译:传统的节点排名算法只需将一个网络的节点排序到网络,并且不指的是网络事件的序列。我们向动态排名对象提出了TVNM,这是一种量化“随时间随时间之间关系的框架。我们还提出了基于TVNM的修改后的PageRank算法。我们将PageRank算法与大型组织数据集的修改后的PageRank算法进行比较。

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