Finding Strongly Correlated Trends in Dynamic Attributed Graphs

Philippe Fournier-Viger, Chao Cheng, Zhi-cheng, Jerry Chun-Wei Lin, Nazha Selmaoui-Folcher. Finding Strongly Correlated Trends in Dynamic Attributed Graphs. In Carlos Ordonez 0001, Il-Yeol Song, Gabriele Anderst-Kotsis, A Min Tjoa, Ismail Khalil, editors, Big Data Analytics and Knowledge Discovery - 21st International Conference, DaWaK 2019, Linz, Austria, August 26-29, 2019, Proceedings. Volume 11708 of Lecture Notes in Computer Science, pages 250-265, Springer, 2019. [doi]

@inproceedings{Fournier-VigerC19,
  title = {Finding Strongly Correlated Trends in Dynamic Attributed Graphs},
  author = {Philippe Fournier-Viger and Chao Cheng and Zhi-cheng and Jerry Chun-Wei Lin and Nazha Selmaoui-Folcher},
  year = {2019},
  doi = {10.1007/978-3-030-27520-4_18},
  url = {https://doi.org/10.1007/978-3-030-27520-4_18},
  researchr = {https://researchr.org/publication/Fournier-VigerC19},
  cites = {0},
  citedby = {0},
  pages = {250-265},
  booktitle = {Big Data Analytics and Knowledge Discovery - 21st International Conference, DaWaK 2019, Linz, Austria, August 26-29, 2019, Proceedings},
  editor = {Carlos Ordonez 0001 and Il-Yeol Song and Gabriele Anderst-Kotsis and A Min Tjoa and Ismail Khalil},
  volume = {11708},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-030-27520-4},
}