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SPARK: Top-k Keyword Query in Relational Databases

Summary: Introduces SPARK for top-k keyword queries over relational data using a virtual-document ranking that adapts IR techniques. Proposes efficient processing with minimal DB accesses; shows strong effectiveness and efficiency on large real datasets across two RDBMS. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
hbf972985f0f04e80
Venue
SIGMOD
Year
2007
Pagerank
0.00012950177
Overall Rank
942 | 93.68%
DOI
10.1145/1247480.1247495

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{luo_sigmod07,
        title = {{SPARK: Top-k Keyword Query in Relational Databases}},
        author = {Luo, Yi and Lin, Xuemin and Wang, Wei and Zhou, Xiaofang},
        series = {{SIGMOD} '07},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1247480.1247495},
        url = {https://dl.acm.org/doi/10.1145/1247480.1247495},
        year = {2007}
}

Incoming Citations (Sorted by Pagerank)

Showing 32 of 32 citing papers.

Rank Citing Paper Year Venue Pagerank
1,273 Discovering Queries based on Example Tuples 2014 SIGMOD 0.00011243661
1,501 Keyword Search in Databases: The Power of RDBMS 2009 SIGMOD 0.00010456517
1,907 EASE: An Effective 3-in-1 Keyword Search Method for Unstructured, Semi-structured and Structured Data 2008 SIGMOD 9.3936687e-05
2,413 S4: Top-k Spreadsheet-Style Search for Query Discovery 2015 SIGMOD 8.5063082e-05
2,415 Structured Search Result Differentiation 2009 VLDB 8.5041001e-05
3,172 Toward Computational Fact-Checking 2014 VLDB 7.5658423e-05
3,313 Keyword Search on Structured and Semi-Structured Data 2009 SIGMOD 7.4350441e-05
3,509 Keyword Search on External Memory Data Graphs 2008 VLDB 7.24401e-05
3,730 Keyword Search over Relational Databases: A Metadata Approach 2011 SIGMOD 7.0663712e-05
4,141 Efficient Type-Ahead Search on Relational Data: a TASTIER Approach 2009 SIGMOD 6.7822757e-05
4,468 Schemaless and Structureless Graph Querying 2014 VLDB 6.5841276e-05
4,809 Finding Patterns in a Knowledge Base using Keywords to Compose Table Answers 2014 VLDB 6.4051922e-05
4,844 REX: Explaining Relationships between Entity Pairs 2012 VLDB 6.3811116e-05
5,156 An In-Depth Benchmarking of Text-to-SQL Systems 2021 SIGMOD 6.2475361e-05
5,280 Top-K Structural Diversity Search in Large Networks 2013 VLDB 6.1970455e-05
5,351 Query Biased Snippet Generation in XML Search 2008 SIGMOD 6.166804e-05
5,511 SiriusBI: A Comprehensive LLM-Powered Solution for Data Analytics in Business Intelligence 2025 VLDB 6.0968143e-05
6,902 Keyword Query Cleaning 2008 VLDB 5.6493762e-05
7,149 Effective and Efficient Retrieval of Structured Entities 2020 VLDB 5.5966554e-05
8,188 Full-Power Graph Querying: State of the Art and Challenges 2023 VLDB 5.3795421e-05
8,448 Diverse and Proportional Size-l Object Summaries for Keyword Search 2015 SIGMOD 5.3324907e-05
8,824 ARCube: Supporting Ranking Aggregate Queries in Partially Materialized Data Cubes 2008 SIGMOD 5.2685089e-05
9,108 Toward Scalable Keyword Search over Relational Data 2010 VLDB 5.2258409e-05
9,600 Size-l Object Summaries for Relational Keyword Search 2012 VLDB 5.1539819e-05
9,980 A Graph Method for Keyword-based Selection of the top-K Databases 2008 SIGMOD 5.1009087e-05
10,021 The Data Interaction Game 2018 SIGMOD 5.0935279e-05
12,081 Analysis of Database Search Systems with THOR 2020 SIGMOD 4.9769913e-05
12,420 Proactive Annotation Management in Relational Databases 2015 SIGMOD 4.9769913e-05
12,584 Probabilistic Query Rewriting for Efficient and Effective Keyword Search on Graph Data 2013 VLDB 4.9769913e-05
12,682 Keyword Search on Form Results 2011 VLDB 4.9769913e-05
12,758 Ten Thousand SQLs: Parallel Keyword Queries Computing 2010 VLDB 4.9769913e-05
12,774 Searching Workflows with Hierarchical Views 2010 VLDB 4.9769913e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 15 of 15 cited papers.

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

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