Link prediction with social vector clocks
Link prediction with social vector clocks
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DOI：
10.1145/2487575.2487615
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发表时间：
2013-04
期刊：
影响因子：
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通讯作者：
Conrad Lee;B. Nick;U. Brandes;P. Cunningham
中科院分区：
文献类型：
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作者：
Conrad Lee;B. Nick;U. Brandes;P. Cunningham
最先进的链路预测利用从网络面板数据派生的复杂特征的组合。我们在这里展示了在数据作为交互序列可用的常见场景中，计算成本较低的功能可以实现相同的性能。我们的功能基于社交矢量钟，这是分布式计算中引入的矢量钟概念在社交交互网络中的改编。事实上，我们的实验表明，通过考虑互动的顺序和间隔，社交矢量时钟利用了链接形成的不同方面，因此它们与以前的方法相结合，产生了迄今为止最准确的预测。
State-of-the-art link prediction utilizes combinations of complex features derived from network panel data. We here show that computationally less expensive features can achieve the same performance in the common scenario in which the data is available as a sequence of interactions. Our features are based on social vector clocks, an adaptation of the vector-clock concept introduced in distributed computing to social interaction networks. In fact, our experiments suggest that by taking into account the order and spacing of interactions, social vector clocks exploit different aspects of link formation so that their combination with previous approaches yields the most accurate predictor to date.