SVM in Oracle Database 10g: Removing the Barriers to Widespread Adoption of Support Vector Machines
Summary: Oracle Database 10g embeds SVM, bringing data mining into the DBMS to remove usability and scalability barriers. Emphasizes ease of use, production-grade accuracy, and seamless, in-database deployment across analytic workloads. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Boriana L. Milenova (Oracle)
- 2. Joseph S. Yarmus (Oracle)
- 3. Marcos M. Campos (Oracle)
BibTeX Citation
@article{milenova_vldb05,
title = {{SVM in Oracle Database 10g: Removing the Barriers to Widespread Adoption of Support Vector Machines}},
author = {Milenova, Boriana L. and Yarmus, Joseph S. and Campos, Marcos M.},
journal = {PVLDB},
series = {{VLDB} '05},
pages = {1152--1163},
year = {2005}
}Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 518 | Towards a Unified Architecture for in-RDBMS Analytics | 2012 | SIGMOD | 0.00017167492 |
| 3,682 | In-RDBMS Hardware Acceleration of Advanced Analytics | 2018 | VLDB | 7.2035518e-05 |
| 5,695 | Incrementally Maintaining Classification using an RDBMS | 2011 | VLDB | 6.1183313e-05 |
| 11,576 | Interactive Mining with Ordered and Unordered Attributes | 2022 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 0 of 0 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|
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