Data-Driven Domain Discovery for Structured Datasets
Summary: Data-driven domain discovery across heterogeneous tables uses cross-column value co-occurrence to derive context signatures and infer attribute domains. Robust to incomplete or noisy data, scales to millions of terms, and outperforms state-of-the-art on real urban datasets, enabling richer queries and integration. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Masayo Ota (New York University)
- 2. Heiko Müller (New York University)
- 3. Juliana Freire (New York University)
- 4. Divesh Srivastava (AT&T)
BibTeX Citation
@article{ota_vldb20,
title = {{Data-Driven Domain Discovery for Structured Datasets}},
author = {Ota, Masayo and Müller, Heiko and Freire, Juliana and Srivastava, Divesh},
journal = {PVLDB},
series = {{VLDB} '20},
volume = {13},
number = {7},
pages = {953--965},
doi = {10.14778/3384345.3384346},
url = {https://doi.org/10.14778/3384345.3384346},
year = {2020}
}Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,780 | Annotating Columns with Pre-trained Language Models | 2022 | SIGMOD | 9.6560923e-05 |
| 1,852 | Semantics-aware Dataset Discovery from Data Lakes with Contextualized Column-based Representation Learning | 2023 | VLDB | 9.5004635e-05 |
| 1,988 | SANTOS: Relationship-based Semantic Table Union Search | 2023 | SIGMOD | 9.2482448e-05 |
| 4,589 | ArcheType: A Novel Framework for Open-Source Column Type Annotation using Large Language Models | 2024 | VLDB | 6.5144711e-05 |
| 7,197 | Cross Modal Data Discovery over Structured and Unstructured Data Lakes | 2023 | VLDB | 5.5890662e-05 |
| 7,643 | TableDC: Deep Clustering for Tabular Data | 2025 | SIGMOD | 5.4772833e-05 |
| 11,323 | LakeVisage: Towards Scalable, Flexible and Interactive Visualization Recommendation for Data Discovery over Data Lakes | 2025 | VLDB | 4.9793485e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 367 | InfoGather: Entity Augmentation and Attribute Discovery By Holistic Matching with Web Tables | 2012 | SIGMOD | 0.00019884846 |
| 509 | Goods: Organizing Google's Datasets | 2016 | SIGMOD | 0.00017071087 |
| 624 | Data Lake Management: Challenges and Opportunities | 2019 | VLDB | 0.00015479826 |
| 765 | Table Union Search on Open Data | 2018 | VLDB | 0.00014125424 |
| 2,190 | Data Integration: After the Teenage Years | 2017 | PODS | 8.8867887e-05 |
| 2,924 | Constance: An Intelligent Data Lake System | 2016 | SIGMOD | 7.8498312e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 6,428 | Domain-Aware Multi-Truth Discovery from Conflicting Sources | 2018 | VLDB |
| 2 | 757 | Recovering Semantics of Tables on the Web | 2011 | VLDB |
| 3 | 11,038 | Semantic Data Systems: From Data Management to Data Understanding | 2026 | VLDB |
| 4 | 3,470 | Automatic Discovery of Attributes in Relational Databases | 2011 | SIGMOD |
| 5 | 765 | Table Union Search on Open Data | 2018 | VLDB |
| 6 | 4,306 | Discovering Topical Structures of Databases | 2008 | SIGMOD |
| 7 | 7,197 | Cross Modal Data Discovery over Structured and Unstructured Data Lakes | 2023 | VLDB |
| 8 | 12,278 | Building Structured Databases of Factual Knowledge from Massive Text Corpora | 2017 | SIGMOD |
| 9 | 9,857 | Attribute Domain Discovery for Hidden Web Databases | 2011 | SIGMOD |
| 10 | 12,709 | Schema Clustering and Retrieval for Multi-domain Pay-As-You-Go Data Integration Systems | 2010 | SIGMOD |