Interactive View Recommendation
Summary: ViewSeeker automatically discovers and composes utility functions for view selection in high-dimensional data. It adapts to user intent during interactive exploration, yielding a tailored mix of utility functions for the task and visualization. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Xiaozhong Zhang (University of Pittsburgh)
BibTeX Citation
@inproceedings{zhang_sigmod20,
title = {{Interactive View Recommendation}},
author = {Zhang, Xiaozhong},
series = {{SIGMOD} '20},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3318464.3384407},
url = {https://dl.acm.org/doi/10.1145/3318464.3384407},
year = {2020}
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 410 | SeeDB: Efficient Data-Driven Visualization Recommendations to Support Visual Analytics | 2015 | VLDB | 0.0001890421 |
| 1,932 | VizDeck: Self-Organizing Dashboards for Visual Analytics | 2012 | SIGMOD | 9.4646634e-05 |
| 3,132 | Extracting Top-K Insights from Multi-dimensional Data | 2017 | SIGMOD | 7.7246394e-05 |
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