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PyExplore: Query Recommendations for Data Exploration without Query Logs

Summary: PyExplore provides query recommendations for data exploration on unseen datasets without relying on historical query logs. It accepts an initial query and parameters, and outputs diverse, data-correlated recommendations to guide exploration. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6106
Venue
SIGMOD
Year
2021
Pagerank
5.093636e-05
Overall Rank
11,661 | 20.00%
DOI
10.1145/3448016.3452762

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

BibTeX Citation

@inproceedings{glenis_sigmod21,
        title = {{PyExplore: Query Recommendations for Data Exploration without Query Logs}},
        author = {Glenis, Apostolos and Koutrika, Georgia},
        series = {{SIGMOD} '21},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3448016.3452762},
        url = {https://dl.acm.org/doi/10.1145/3448016.3452762},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
11,719 DatAgent: The Imminent Age of Intelligent Data Assistants 2021 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
291 OPTICS: Ordering Points To Identify the Clustering Structure 1999 SIGMOD 0.00022264197
846 SnipSuggest: Context-Aware Autocompletion for SQL 2011 VLDB 0.00013658824
4,196 Automatic Example Queries for Ad Hoc Databases 2011 SIGMOD 6.8416684e-05
4,395 Automating Exploratory Data Analysis via Machine Learning: An Overview 2020 SIGMOD 6.7271323e-05
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