An Interval Classifier for Database Mining Applications
Summary: Introduces an interval classifier that learns group-specific retrieval functions from a small labeled sample to classify a large unlabeled population database. Optimized for interactive ad hoc queries and missing values, it offers fast model generation/retrieval with accuracy competitive with ID3. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Rakesh Agrawal (IBM)
- 2. Sakti Ghosh (IBM)
- 3. Tomasz Imielinski (IBM; Rutgers University)
- 4. Bala Iyer (IBM)
- 5. Arun Swami (IBM)
BibTeX Citation
@article{agrawal_vldb92,
title = {{An Interval Classifier for Database Mining Applications}},
author = {Agrawal, Rakesh and Ghosh, Sakti and Imielinski, Tomasz and Iyer, Bala and Swami, Arun},
journal = {PVLDB},
series = {{VLDB} '92},
pages = {560--573},
year = {1992}
}
Incoming Citations (Sorted by Pagerank)
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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.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 45 | Benchmarking Database Systems: A Systematic Approach | 1983 | VLDB | 0.00045531113 |
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| 1 | 1,907 | Incremental Clustering for Mining in a Data Warehousing Environment | 1998 | VLDB |
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| 4 | 12,757 | Efficiently Processing Queries on Interval-and-Value Tuples in Relational Databases | 2005 | VLDB |
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| 6 | 9,874 | Fast Search-By-Classification for Large-Scale Databases Using Index-Aware Decision Trees and Random Forests | 2023 | VLDB |
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| 8 | 5,695 | Incrementally Maintaining Classification using an RDBMS | 2011 | VLDB |
| 9 | 4,545 | Association Rules over Interval Data | 1997 | SIGMOD |
| 10 | 4,842 | Mining Relationships Among Interval-based Events for Classification | 2008 | SIGMOD |