ChiSeL: Graph Similarity Search using Chi-Squared Statistics in Large Probabilistic Graphs
Summary: ChiSeL enables subgraph similarity search in large probabilistic graphs via chi-square scores for candidate vertex matches. Greedy expansion prioritizes high chi-square matches, handling edge, label, and vertex uncertainty; validated on real data. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Shubhangi Agarwal (Indian Institute of Technology)
- 2. Sourav Dutta (Huawei Research Centre)
- 3. Arnab Bhattacharya (Indian Institute of Technology)
BibTeX Citation
@article{agarwal_vldb20,
title = {{ChiSeL: Graph Similarity Search using Chi-Squared Statistics in Large Probabilistic Graphs}},
author = {Agarwal, Shubhangi and Dutta, Sourav and Bhattacharya, Arnab},
journal = {PVLDB},
series = {{VLDB} '20},
volume = {13},
number = {10},
pages = {1654--1668},
doi = {10.14778/3401960.3401964},
url = {https://doi.org/10.14778/3401960.3401964},
year = {2020}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,281 | Sage: A System for Uncertain Network Analysis | 2022 | VLDB | 5.2933125e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 21 of 21 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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