Influential Community Search over Large Heterogeneous Information Networks
Summary: Introduces heterogeneous influential communities (HICs): same-type, tightly connected vertices with type-specific importance, modeled via meta-path-based cores. Peeling, key-vertex identification, and pruning enable scalable search in large HINs, outperforming baselines. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yingli Zhou (Chinese University of Hong Kong)
- 2. Yixiang Fang (Chinese University of Hong Kong)
- 3. Wensheng Luo (Chinese University of Hong Kong)
- 4. Yunming Ye (Harbin Engineering University)
BibTeX Citation
@article{zhou_vldb23,
title = {{Influential Community Search over Large Heterogeneous Information Networks}},
author = {Zhou, Yingli and Fang, Yixiang and Luo, Wensheng and Ye, Yunming},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {8},
pages = {2047--2060},
doi = {10.14778/3594512.3594532},
url = {https://doi.org/10.14778/3594512.3594532},
year = {2023}
}
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