Temporal Link Prediction Based on Dynamic Heterogeneous Information Network
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摘要: 动态异构信息网络中的时序关系预测问题近些年被广泛研究，时序关系预测旨在预测关系产生时间的同时预测关系的类型.动态异构信息网络是包含不同类型的点和边且边上带有时间信息的网络.现有的方法主要考虑了网络中拓扑结构对于关系预测的影响，而并未将时间和结构信息整合到一个统一的模型中进行研究.针对以上问题，提出了一个时间差关系路径法(time-difference-labeled path, TDLP)用于实现时序关系预测，该方法将网络中边上的时间信息融入到结构路径中从而得到更好的预测效果.在一个学术网络上的实验证明，提出的TDLP方法相比当前流行的方法具有更高预测准确率.Abstract: Temporal link prediction on dynamic heterogeneous information networks, aiming to predict both the building times of links and their types, has been widely studied in recent years. The dynamic heterogeneous information network is a network that has different types of vertices and time-labeled edges, and in this paper we study the temporal link prediction problem in the dynamic heterogeneous information network. Most existing studies employs the structure-based predictive methods, where the structures fails to embed the time information. Therefore, they cannot characterize the correlation between structures and time during the prediction. In this work, we firstly construct the structure called the time-difference-labeled path(TDLP) to combine the time information and structural features into a unified setting and propose TDLP, a time-difference-labeled path based temporal link prediction method, which combines the time information with the structural path features. Experiments on a real data set of a scholar bibliographic website demonstrate that the proposed TDLP method performs better than the state-of-the-art methods on predicting both whether and when a link will be built.
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