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Minimization of Classifier Construction Cost for Search Queries

Summary: Minimize classifier construction cost for search over massive item sets by selecting which classifiers to train under non-uniform costs. Proves NP-hard inapproximability; presents approximation algorithms with guarantees and an exact algorithm for a common special case, validated on real data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6032
Venue
SIGMOD
Year
2020
Pagerank
5.093636e-05
Overall Rank
11,790 | 19.11%
DOI
10.1145/3318464.3389755

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

BibTeX Citation

@inproceedings{gershtein_sigmod20,
        title = {{Minimization of Classifier Construction Cost for Search Queries}},
        author = {Gershtein, Shay and Milo, Tova and Morami, Gefen and Novgorodov, Slava},
        series = {{SIGMOD} '20},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3318464.3389755},
        url = {https://dl.acm.org/doi/10.1145/3318464.3389755},
        year = {2020}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
10,112 Classifier Construction Under Budget Constraints 2022 SIGMOD 5.1319012e-05
11,777 MC3: A System for Minimization of Classifier Construction Cost 2020 SIGMOD 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

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

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