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Watchog: A Light-weight Contrastive Learning based Framework for Column Annotation
Summary: Watchog uses contrastive learning on an unlabeled table corpus to yield robust representations for column annotation with few labels. Semi-supervised optimizations mitigate imbalance, delivering Micro/Macro F1 gains on semantic-type detection.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 6773
- Venue
- SIGMOD
- Year
- 2023
- Pagerank
- 4.4356508e-05
- Overall Rank
- 8,852 | 38.42%
- DOI
-
10.1145/3626766
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 12 of 12 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 107 |
WebTables: Exploring the Power of Tables on the Web |
2008 |
VLDB |
0.00048377684 |
| 364 |
Annotating and Searching Web Tables Using Entities, Types and Relationships |
2010 |
VLDB |
0.00025637562 |
| 513 |
TURL: Table Understanding through Representation Learning |
2021 |
VLDB |
0.00021288342 |
| 2,517 |
Annotating Columns with Pre-trained Language Models |
2022 |
SIGMOD |
8.6092139e-05 |
| 2,836 |
Semantics-aware Dataset Discovery from Data Lakes with Contextualized Column-based Representation Learning |
2023 |
VLDB |
8.0443826e-05 |
| 2,888 |
Sato: Contextual Semantic Type Detection in Tables |
2020 |
VLDB |
7.9594996e-05 |
| 3,520 |
GitTables: A Large-Scale Corpus of Relational Tables |
2023 |
SIGMOD |
7.0131061e-05 |
| 4,967 |
Leva: Boosting Machine Learning Performance with Relational Embedding Data Augmentation |
2022 |
SIGMOD |
5.7956612e-05 |
| 5,449 |
Transformers for Tabular Data Representation: A Tutorial on Models and Applications |
2022 |
VLDB |
5.5008652e-05 |
| 5,978 |
Rotom: A Meta-Learned Data Augmentation Framework for Entity Matching, Data Cleaning, Text Classification, and Beyond |
2021 |
SIGMOD |
5.2453012e-05 |
| 7,052 |
Pre-trained Embeddings for Entity Resolution: An Experimental Analysis |
2023 |
VLDB |
4.8497453e-05 |
| 9,777 |
Data Augmentation for ML-driven Data Preparation and Integration |
2021 |
VLDB |
4.2856106e-05 |
Semantically Similar Papers
| Overall Rank |
Paper |
Year |
Venue |
Pagerank |
| 6,092 |
Observatory: Characterizing Embeddings of Relational Tables |
2024 |
VLDB |
5.2138566e-05 |
| 364 |
Annotating and Searching Web Tables Using Entities, Types and Relationships |
2010 |
VLDB |
0.00025637562 |
| 5,099 |
ArcheType: A Novel Framework for Open-Source Column Type Annotation using Large Language Models |
2024 |
VLDB |
5.6997784e-05 |
| 2,888 |
Sato: Contextual Semantic Type Detection in Tables |
2020 |
VLDB |
7.9594996e-05 |
| 3,229 |
InfoGather+: Semantic Matching and Annotation of Numeric and Time-Varying Attributes in Web Tables |
2013 |
SIGMOD |
7.3393682e-05 |
| 1,367 |
Answering Table Queries on the Web using Column Keywords |
2012 |
VLDB |
0.00012349783 |
| 1,001 |
Recovering Semantics of Tables on the Web |
2011 |
VLDB |
0.00014706505 |
| 2,517 |
Annotating Columns with Pre-trained Language Models |
2022 |
SIGMOD |
8.6092139e-05 |
| 10,109 |
Retrieve-and-Verify: A Table Context Selection Framework for Accurate Column Annotations |
2026 |
SIGMOD |
4.1945683e-05 |
| 8,579 |
RECA: Related Tables Enhanced Column Semantic Type Annotation Framework |
2023 |
VLDB |
4.4922446e-05 |