/Temp-GFSM

Meta-Learned Metrics over Multi-Evolution Temporal Graphs, KDD 2022

Temp-GFSM: Meta-Learned Metrics over Multi-Evolution Temporal Graphs

This repository is for the KDD' 2022 paper "Meta-Learned Metrics over Multi-Evolution Temporal Graphs" (Link) .

Functionality

Temp-GFSM first models temporal graphs for multiple dynamic evolution pattern, then it learns the accurate and adaptive metrics over them via the representation learning techniques.

Reference

If you use the materials from this repositiory, please refer to our paper.

@inproceedings{DBLP:conf/kdd/FuFMTH22,
  author    = {Dongqi Fu and
               Liri Fang and
               Ross Maciejewski and
               Vetle I. Torvik and
               Jingrui He},
  editor    = {Aidong Zhang and
               Huzefa Rangwala},
  title     = {Meta-Learned Metrics over Multi-Evolution Temporal Graphs},
  booktitle = {{KDD} '22: The 28th {ACM} {SIGKDD} Conference on Knowledge Discovery
               and Data Mining, Washington, DC, USA, August 14 - 18, 2022},
  pages     = {367--377},
  publisher = {{ACM}},
  year      = {2022},
  url       = {https://doi.org/10.1145/3534678.3539313},
  doi       = {10.1145/3534678.3539313},
  timestamp = {Mon, 15 Aug 2022 14:53:46 +0200},
  biburl    = {https://dblp.org/rec/conf/kdd/FuFMTH22.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}