Database Paper Browser

Back to papers

TableDC: Deep Clustering for Tabular Data

Summary: TableDC applies deep clustering to tabular data, learning embeddings for schemas, rows, and domains. It blends Mahalanobis distance with a heavy-tailed Cauchy kernel to handle overlap/outliers and scales to many clusters for data integration. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
7280
Venue
SIGMOD
Year
2025
Pagerank
4.8925595e-05
Overall Rank
6,894 | 52.05%
DOI
10.1145/3725366

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
10,060 Categorical Data Clustering via Value Order Estimated Distance Metric Learning 2026 SIGMOD 4.1945683e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 14 of 14 cited papers.

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

Previous Page 1 / 1 Next

Semantically Similar Papers