S4: Top-k Spreadsheet-Style Search for Query Discovery
Summary: S4 proposes top-k project-join query discovery with approximate containment of user-provided example tuples. It enables spreadsheet-style, incremental search that returns results as users type or edit a cell, delivering substantial efficiency gains over prior state-of-the-art. (summarized by gpt-5-nano on Feb 09 2026)
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,410 | Efficient Type-Ahead Search on Relational Data: a TASTIER Approach | 2009 | SIGMOD | 6.2012075e-05 |
| 802 | Evaluating Top-k Selection Queries | 1999 | VLDB | 0.00016440813 |
| 53 | DISCOVER: Keyword Search in Relational Databases | 2002 | VLDB | 0.00065993143 |
| 278 | Efficient IR-Style Keyword Search over Relational Databases | 2003 | VLDB | 0.00029322862 |
| 12,143 | Answering Top-k Queries Over a Mixture of Attractive and Repulsive Dimensions | 2012 | VLDB | 4.1905499e-05 |
| 3,665 | Ad-hoc Top-k Query Answering for Data Streams | 2007 | VLDB | 6.8631567e-05 |
| 8,132 | Discovering the Skyline of Web Databases | 2016 | VLDB | 4.5741104e-05 |
| 12,119 | Optimal Top-k Generation of Attribute Combinations based on Ranked Lists | 2012 | SIGMOD | 4.1905499e-05 |
| 7,660 | Processing Top-k Join Queries | 2010 | VLDB | 4.6814547e-05 |
| 1,502 | Discovering Queries based on Example Tuples | 2014 | SIGMOD | 0.00011614522 |