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Towards Plug-and-Play Visual Graph Query Interfaces: Data-driven Selection of Canned Patterns for Large Networks

Summary: Tattoo automatically derives canned subgraph patterns for visual querying of large networks, replacing laborious domain-expert selection. It mines truss-infested/oblivious regions and optimizes plug-specific pattern sets for coverage, diversity, and cognitive load. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
12567
Venue
VLDB
Year
2021
Pagerank
5.7507099e-05
Overall Rank
6,866 | 52.90%
DOI
10.14778/3476249.3476256

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{yuan_vldb21,
        title = {{Towards Plug-and-Play Visual Graph Query Interfaces: Data-driven Selection of Canned Patterns for Large Networks}},
        author = {Yuan, Zifeng and Chua, Huey Eng and Bhowmick, Sourav S and Ye, Zekun and Han, Wook-Shin and Choi, Byron},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {11},
        pages = {1979--1991},
        doi = {10.14778/3476249.3476256},
        url = {https://doi.org/10.14778/3476249.3476256},
        year = {2021}
}

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