In the recent years, reciprocal link prediction has received some attention from the data mining and social network anal- ysis researchers, who solved this problem as a binary clas- sification task. However, it is also important to predict the interval time for the creation of reciprocal link. This is a chal- lenging problem for two reasons: First, the lack of effective features, because well-known link prediction features are de- signed for undirected networks and for the binary classifica- tion task, hence they do not work well for the interval time prediction; Second, the presence of censored data instances makes the traditional supervised regression methods unsuit- able for solving this problem. In this paper, we propose a solution for the reciprocal link interval time prediction task. We map this problem into survival analysis framework and show through extensive experiments on real-world datasets that, survival analysis methods perform better than traditional regression , neural network based model and support vector regression (SVR).
Vachik S. Dave, Mohammad Al Hasan, Chandan K. Reddy: How Fast Will You Get a Response? Predicting Interval Time for Reciprocal Link Creation. ICWSM2017: 508-511
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- AAAI Conference on Web and Social Media
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