TabJoinBench: A Benchmark for Joinable Table Discovery
Join discovery aims to identify tables from large data repositories that can augment a query table with complementary information, enabling downstream tasks such as data exploration, feature engineering, and business intelligence. Although numerous join discovery methods have been proposed, existing studies rely on method-specific benchmark construction, making reproducible and fair comparison difficult. We present TabJoinBench, a benchmark for evaluating join discovery methods across semantic, relational, and hybrid data lake scenarios. TabJoinBench constructs query-candidate pairs using source-specific validation strategies, systematically introduces structural, representation, and sema...
| Authors | Sandipan De, Jin Wang, Vivek Gupta |
|---|---|
| Primary category | cs.DB |
| Published | 30 September 2026 |
| Last updated at source | 30 September 2026 |
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