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GRASS

source code for paper "GRASS: Learning Spatial-Temporal Properties from Chain-like Cascade Data for Diffusion Prediction"

Description

We provide the checkpoints and result files.

For validation, please input:

python run.py --data=memetracker --save_path=./checkpoints/GRASS_memetracker.pt

The code of this project is developed based on the following two articles.


@inproceedings{DBLP:conf/dasfaa/WangWYBZZH22,
  author    = {Ding Wang and
               Lingwei Wei and
               Chunyuan Yuan and
               Yinan Bao and
               Wei Zhou and
               Xian Zhu and
               Songlin Hu},
  title     = {Cascade-Enhanced Graph Convolutional Network for Information Diffusion
               Prediction},
  booktitle = {Database Systems for Advanced Applications - 27th International Conference,
               {DASFAA} 2022, Virtual Event, April 11-14, 2022, Proceedings, Part
               {I}},
  series    = {Lecture Notes in Computer Science},
  volume    = {13245},
  pages     = {615--631},
  publisher = {Springer},
  year      = {2022},
  url       = {https://doi.org/10.1007/978-3-031-00123-9\_50},
  doi       = {10.1007/978-3-031-00123-9\_50},
  timestamp = {Fri, 29 Apr 2022 14:50:40 +0200},
  biburl    = {https://dblp.org/rec/conf/dasfaa/WangWYBZZH22.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{ijcai2019-560,
  title     = {Multi-scale Information Diffusion Prediction with Reinforced Recurrent Networks},
  author    = {Yang, Cheng and Tang, Jian and Sun, Maosong and Cui, Ganqu and Liu, Zhiyuan},
  booktitle = {Proceedings of the Twenty-Eighth International Joint Conference on
               Artificial Intelligence, {IJCAI-19}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},             
  pages     = {4033--4039},
  year      = {2019},
  month     = {7},
  doi       = {10.24963/ijcai.2019/560},
  url       = {https://doi.org/10.24963/ijcai.2019/560},
}