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Size-l Object Summaries for Relational Keyword Search

Summary: Defines size-l Object Summaries (size-l OSs) as a partial, stand-alone synopsis of a Data Subject, built from l important tuples in relational keyword search. Proposes three efficient generation algorithms (with an exponential-time optimal baseline) and validates effectiveness on DBLP and TPC-H. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10661
Venue
VLDB
Year
2012
Pagerank
5.2745733e-05
Overall Rank
9,413 | 35.42%
DOI
10.14778/2072231.2072232

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{fakas_vldb12,
        title = {{Size-l Object Summaries for Relational Keyword Search}},
        author = {Fakas, Georgios J. and Cai, Zhi and Mamoulis, Nikos},
        journal = {PVLDB},
        series = {{VLDB} '12},
        volume = {5},
        number = {3},
        pages = {229--240},
        doi = {10.14778/2072231.2072232},
        url = {https://doi.org/10.14778/2072231.2072232},
        year = {2012}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
2,631 FastQRE: Fast Query Reverse Engineering 2018 SIGMOD 8.3231158e-05
8,273 Diverse and Proportional Size-l Object Summaries for Keyword Search 2015 SIGMOD 5.4574671e-05
11,676 Proportionality in Spatial Keyword Search 2021 SIGMOD 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 10 of 10 cited papers.

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

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