Periodic Community Search in Temporal Graphs: Time Series-based Methods
Summary: Introduces k-core time-series similarity to detect periodicity in temporal graphs and defines local periodic community search by pattern frequency. TD and VD algorithms exploit temporal monotonicity, TP-Core indexing, and vertex pruning to avoid exponential subset enumeration. (summarized by gpt-5.6-luna on Jul 26 2026)
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Authors
- 1. Yu Chen (Zhejiang University)
- 2. Qing Liu (Zhejiang University)
- 3. Chengyang Luo (Zhejiang University)
- 4. Yunjun Gao (Zhejiang University)
BibTeX Citation
@inproceedings{chen_sigmod26,
title = {{Periodic Community Search in Temporal Graphs: Time Series-based Methods}},
author = {Chen, Yu and Liu, Qing and Luo, Chengyang and Gao, Yunjun},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3802099},
url = {https://dl.acm.org/doi/10.1145/3802099},
year = {2026}
}
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