Fonduer: Knowledge Base Construction from Richly Formatted Data

Summary: Fonduer enables KBC from richly formatted data, beyond traditional inputs. It defines a data model for document-level relations, multimodality, and data variety, plus a deep-learning representation and a supervision-driven programming model. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 5511
Venue: SIGMOD
Year: 2018
Pagerank: 7.65035e-05
Overall Rank: 3,192 | 78.11%
DOI: 10.1145/3183713.3183729

Incoming Non-self Citations Over Time

Authors

1. Sen Wu (Stanford University)
2. Luke Hsiao (Stanford University)
3. Xiao Cheng (Stanford University)
4. Braden Hancock (Stanford University)
5. Theodoros Rekatsinas (University of Wisconsin)
6. Philip Levis (Stanford University)
7. Christopher Ré (Stanford University)

BibTeX Citation

@inproceedings{wu_sigmod18,
        title = {{Fonduer: Knowledge Base Construction from Richly Formatted Data}},
        author = {Wu, Sen and Hsiao, Luke and Cheng, Xiao and Hancock, Braden and Rekatsinas, Theodoros and Levis, Philip and Ré, Christopher},
        series = {{SIGMOD} '18},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3183713.3183729},
        url = {https://dl.acm.org/doi/10.1145/3183713.3183729},
        year = {2018}
}

Incoming Citations (Sorted by Pagerank)

Showing 11 of 11 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
176	Deep Learning for Entity Matching: A Design Space Exploration	2018	SIGMOD	0.00027191081
1,094	Snuba: Automating Weak Supervision to Label Training Data	2019	VLDB	0.00012214617
4,100	Data Integration and Machine Learning: A Natural Synergy	2018	SIGMOD	6.9016092e-05
7,424	Data Integration and Machine Learning: A Natural Synergy	2018	VLDB	5.6214566e-05
7,482	Table Extraction and Understanding for Scientific and Enterprise Applications	2020	VLDB	5.6078973e-05
8,677	Visual Segmentation for Information Extraction from Heterogeneous Visually Rich Documents	2019	SIGMOD	5.3867222e-05
9,398	Improving Information Extraction from Visually Rich Documents using Visual Span Representations	2021	VLDB	5.2755515e-05
9,399	Glean: Structured Extractions from Templatic Documents	2021	VLDB	5.2755515e-05
9,560	Ground Truth Inference for Weakly Supervised Entity Matching	2023	SIGMOD	5.2528121e-05
11,455	Self-Training for Label-Efficient Information Extraction from Semi-Structured Web-Pages	2023	VLDB	5.093636e-05
11,831	ARQuery: Hallucinating Analytics over Real-World Data using Augmented Reality	2019	CIDR	5.093636e-05

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
65	Freebase: A Collaboratively Created Graph Database For Structuring Human Knowledge	2008	SIGMOD	0.00038697603
205	Snorkel: Rapid Training Data Creation with Weak Supervision	2018	VLDB	0.00025235185
579	Incremental Knowledge Base Construction Using DeepDive	2015	VLDB	0.00016217563

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