ML Anthology

Evolution of Node Behavior in Link Prediction

Baojun Qiu, Qi He, John Yen
AAAI 2011 pp. 1810-1811
doi:10.1609/AAAI.V25I1.8038 /aaai/2011/qiu2011aaai-evolution/

Abstract

Link prediction is one of central tasks in the study of social network evolution and has many applications. In this paper, we use time series to describe node behavior, extract temporal features from the time series to characterize behavior evolution of nodes, and use the temporal features for link prediction. Our experimental results on several real datasets suggest that including the temporal features developed in the paper significantly improve link prediction performance.

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Cite

Text

Qiu et al. "Evolution of Node Behavior in Link Prediction." AAAI Conference on Artificial Intelligence, 2011. doi:10.1609/AAAI.V25I1.8038

Markdown

[Qiu et al. "Evolution of Node Behavior in Link Prediction." AAAI Conference on Artificial Intelligence, 2011.](https://mlanthology.org/aaai/2011/qiu2011aaai-evolution/) doi:10.1609/AAAI.V25I1.8038

BibTeX

@inproceedings{qiu2011aaai-evolution,
  title     = {{Evolution of Node Behavior in Link Prediction}},
  author    = {Qiu, Baojun and He, Qi and Yen, John},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2011},
  pages     = {1810-1811},
  doi       = {10.1609/AAAI.V25I1.8038},
  url       = {https://mlanthology.org/aaai/2011/qiu2011aaai-evolution/}
}