MIDAS: Towards Efficient and Effective Maintenance of Canned Patterns in Visual Graph Query Interfaces
Summary: MIDAS maintains canned subgraph patterns in visual graph query GUIs as graphs evolve. A selective maintenance strategy yields progressive coverage while preserving diversity and cognitive load, outperforming static GUIs on real-world datasets. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Kai Huang (Fudan University; Nanyang Technological University)
- 2. Huey Eng Chua (Nanyang Technological University)
- 3. Sourav S Bhowmick (Nanyang Technological University)
- 4. Byron Choi (Hong Kong Baptist University)
- 5. Shuigeng Zhou (Fudan University)
BibTeX Citation
@inproceedings{huang_sigmod21,
title = {{MIDAS: Towards Efficient and Effective Maintenance of Canned Patterns in Visual Graph Query Interfaces}},
author = {Huang, Kai and Chua, Huey Eng and Bhowmick, Sourav S and Choi, Byron and Zhou, Shuigeng},
series = {{SIGMOD} '21},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3448016.3457251},
url = {https://dl.acm.org/doi/10.1145/3448016.3457251},
year = {2021}
}Incoming Citations (Sorted by Pagerank)
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,934 | Towards Efficient Index Construction and Approximate Nearest Neighbor Search in High-Dimensional Spaces | 2023 | VLDB | 9.4561907e-05 |
| 6,463 | Data-driven Visual Query Interfaces for Graphs: Past, Present, and (Near) Future | 2022 | SIGMOD | 5.871484e-05 |
| 6,866 | Towards Plug-and-Play Visual Graph Query Interfaces: Data-driven Selection of Canned Patterns for Large Networks | 2021 | VLDB | 5.7507099e-05 |
| 9,131 | TED: Towards Discovering Top-k Edge-Diversified Patterns in a Graph Database | 2023 | SIGMOD | 5.3184767e-05 |
| 10,088 | VisualNeo: Bridging the Gap between Visual Query Interfaces and Graph Query Engines | 2023 | VLDB | 5.1558402e-05 |
| 10,089 | VINCENT: Towards Efficient Exploratory Subgraph Search in Graph Databases | 2022 | VLDB | 5.1558402e-05 |
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