Graph Regularized Meta-path Based Transductive Regression in Heterogeneous Information Network

@article{Wan2015GraphRM,
  title={Graph Regularized Meta-path Based Transductive Regression in Heterogeneous Information Network},
  author={Mengting Wan and Yunbo Ouyang and Lance M. Kaplan and Jiawei Han},
  journal={Proceedings of the ... SIAM International Conference on Data Mining. SIAM International Conference on Data Mining},
  year={2015},
  volume={2015},
  pages={918-926}
}
A number of real-world networks are heterogeneous information networks, which are composed of different types of nodes and links. Numerical prediction in heterogeneous information networks is a challenging but significant area because network based information for unlabeled objects is usually limited to make precise estimations. In this paper, we consider a graph regularized meta-path based transductive regression model (Grempt), which combines the principal philosophies of typical graph-based… CONTINUE READING

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