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LPLM: A Neural Language Model for Cardinality Estimation of LIKE-Queries

Summary: LPLM is a neural language model for LIKE-pattern cardinality estimation, with a novel pattern language and distribution for in-between wildcards. A data-generation method trains it; it outperforms prior work on Q-error with similar runtime/memory. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6925
Venue
SIGMOD
Year
2024
Pagerank
5.7826781e-05
Overall Rank
6,760 | 53.63%
DOI
10.1145/3639309

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{aytimur_sigmod24,
        title = {{LPLM: A Neural Language Model for Cardinality Estimation of LIKE-Queries}},
        author = {Aytimur, Mehmet and Reiner, Silvan and Wörteler, Leonard and Chondrogiannis, Theodoros and Grossniklaus, Michael},
        series = {{SIGMOD} '24},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3639309},
        url = {https://dl.acm.org/doi/10.1145/3639309},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 9 of 9 citing papers.

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Outgoing Citations (Sorted by Pagerank)

Showing 21 of 21 cited papers.

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

Rank Cited Paper Year Venue Pagerank
1 Access Path Selection in a Relational Database Management System 1979 SIGMOD 0.0024089429
18 How Good Are Query Optimizers, Really? 2016 VLDB 0.00059284255
84 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035838391
89 On the Propagation of Errors in the Size of Join Results 1991 SIGMOD 0.00035031529
101 Selectivity Estimation Without the Attribute Value Independence Assumption 1997 VLDB 0.00034376651
154 Neo: A Learned Query Optimizer 2019 VLDB 0.00028726181
257 The History of Histograms (abridged) 2003 VLDB 0.00023154793
323 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021264788
388 Preventing Bad Plans by Bounding the Impact of Cardinality Estimation Errors 2009 VLDB 0.00019410042
737 Join Size Estimation Subject to Filter Conditions 2015 VLDB 0.00014490983
802 Random Sampling over Joins Revisited 2018 SIGMOD 0.00013907725
1,122 Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation 2022 VLDB 0.0001209124
1,140 Estimating Alphanumeric Selectivity in the Presence of Wildcards 1996 SIGMOD 0.0001200574
1,427 Substring Selectivity Estimation 1999 PODS 0.00010812749
1,536 Improved Selectivity Estimation by Combining Knowledge from Sampling and Synopses 2018 VLDB 0.00010460864
1,573 Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries 2020 SIGMOD 0.00010328171
2,899 Extending Q-Grams to Estimate Selectivity of String Matching with Low Edit Distance 2007 VLDB 7.97814e-05
3,545 Astrid: Accurate Selectivity Estimation for String Predicates using Deep Learning 2021 VLDB 7.3249967e-05
5,011 Monotonic Cardinality Estimation of Similarity Selection: A Deep Learning Approach 2020 SIGMOD 6.4020848e-05
7,268 Cardinality Estimation of Approximate Substring Queries using Deep Learning 2022 VLDB 5.6597123e-05
8,051 Wander Join: Online Aggregation for Joins 2016 SIGMOD 5.4997517e-05
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