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SPRINT: A Scalable Parallel Classifier for Data Mining

Summary: SPRINT is an out-of-core decision-tree classifier that eliminates in-memory dataset requirements, enabling scalable mining of large databases. Its partitionable design lets many processors collaboratively build one consistent model with strong parallel scalability. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
8564
Venue
VLDB
Year
1996
Pagerank
0.00010628998
Overall Rank
1,485 | 89.82%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{shafer_vldb96,
        title = {{SPRINT: A Scalable Parallel Classifier for Data Mining}},
        author = {Shafer, John and Agrawal, Rakesh and Mehta, Manish},
        journal = {PVLDB},
        series = {{VLDB} '96},
        pages = {544--555},
        year = {1996}
}

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

Rank Cited Paper Year Venue Pagerank
440 An Interval Classifier for Database Mining Applications 1992 VLDB 0.00018409145
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