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Synthesizing Extraction Rules from User Examples with SEER

Summary: SEER enables end-to-end IE by letting users highlight text and synthesize rules from a few examples. It offers rule suggestions users can accept or reject, jump-starting rule development as a data-efficient alternative to large labeled data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5418
Venue
SIGMOD
Year
2017
Pagerank
5.4155551e-05
Overall Rank
8,484 | 41.80%
DOI
10.1145/3035918.3056443

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{hanafi_sigmod17,
        title = {{Synthesizing Extraction Rules from User Examples with SEER}},
        author = {Hanafi, Maeda F. and Abouzied, Azza and Chiticariu, Laura and Li, Yunyao},
        series = {{SIGMOD} '17},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3035918.3056443},
        url = {https://dl.acm.org/doi/10.1145/3035918.3056443},
        year = {2017}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
6,200 New Trends on Exploratory Methods for Data Analytics 2017 VLDB 5.9457282e-05
8,358 Exploring the Data Wilderness through Examples 2019 SIGMOD 5.4446041e-05
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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.

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