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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)

Paper ID
5070
Venue
SIGMOD
Year
2015
Pagerank
8.5066436e-05
Overall Rank
2,577 | 82.10%
DOI
10.1145/2723372.2749452

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Showing 13 of 13 cited papers.

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

Rank Cited Paper Year Venue Pagerank
8 Optimal Aggregation Algorithms for Middleware [Extended Abstract] 2001 PODS 0.0015436578
53 DISCOVER: Keyword Search in Relational Databases 2002 VLDB 0.00065993143
179 Efficient and Extensible Algorithms for Multi Query Optimization 2000 SIGMOD 0.00037637319
278 Efficient IR-Style Keyword Search over Relational Databases 2003 VLDB 0.00029322862
491 Query by Output 2009 SIGMOD 0.00021960753
798 Optimal Multi-Step k-Nearest Neighbor Search 1998 SIGMOD 0.00016484637
1,202 SPARK: Top-k Keyword Query in Relational Databases 2007 SIGMOD 0.0001333126
1,502 Discovering Queries based on Example Tuples 2014 SIGMOD 0.00011614522
1,575 Reverse Engineering Complex Join Queries 2013 SIGMOD 0.00011288804
2,081 Sample-Driven Schema Mapping 2012 SIGMOD 9.58883e-05
2,211 ReStore: Reusing Results of MapReduce Jobs 2012 VLDB 9.2823037e-05
3,709 Multi-Query Optimization in MapReduce Framework 2014 VLDB 6.8211506e-05
4,410 Efficient Type-Ahead Search on Relational Data: a TASTIER Approach 2009 SIGMOD 6.2012075e-05
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