A Superjoin Algorithm for Deductive Databases
Summary: Introduces a Superjoin algorithm for in-memory deductive and relational databases. Multi-key hashing with buffering enables scalable, faster joins on very large relations; fits naturally with top-down Prolog and allows flexible Prolog extensions. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. James A. Thom
- 2. Kotagiri Ramamohanarao
- 3. Lee Naish
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,249 | Fractals for Secondary Key Retrieval | 1989 | PODS | 0.00013044758 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9 | Implementation Techniques For Main Memory Database Systems | 1984 | SIGMOD | 0.0014279444 |
| 30 | Hashing Methods and Relational Algebra Operations | 1984 | VLDB | 0.00078672446 |
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| 6,686 | An Algorithm For Servicing Multi-Relational Queries | 1977 | SIGMOD | 4.9624102e-05 |
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| 441 | Computing Joins Of Relations | 1975 | SIGMOD | 0.00023058395 |