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AutoDDG: Automated Dataset Description Generation using Large Language Models

Summary: AutoDDG generates dataset descriptions for tabular data by combining data-driven content summarization with LLM-based semantic enrichment, targeting missing/inaccurate metadata in data lakes/open portals. Proposes a multi-faceted evaluation (retrieval, reference-based, reference-free, human) and shows improved dataset search/retrieval at scale. (summarized by gpt-5-mini on Apr 11 2026)

Paper ID
7452
Venue
SIGMOD
Year
2026
Pagerank
4.1945683e-05
Overall Rank
10,142 | 29.45%
DOI
10.1145/3786626

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