SCCQL : A Constraint-Based Clustering System
Abstract
This paper presents the first version of a new inductive data-base system called SCCQL. The system performs constraint-based clustering on a relational database. Clustering problems are formulated with a query language, an extension of SQL for clustering that includes must-link and cannot-link constraints. The functioning of the system is explained. As an example of use of this system, an application in the context of microbiology has been developed that is presented here.
Cite
Text
Adam et al. "SCCQL : A Constraint-Based Clustering System." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2013. doi:10.1007/978-3-642-40994-3_54Markdown
[Adam et al. "SCCQL : A Constraint-Based Clustering System." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2013.](https://mlanthology.org/ecmlpkdd/2013/adam2013ecmlpkdd-sccql/) doi:10.1007/978-3-642-40994-3_54BibTeX
@inproceedings{adam2013ecmlpkdd-sccql,
title = {{SCCQL : A Constraint-Based Clustering System}},
author = {Adam, Antoine and Blockeel, Hendrik and Govers, Sander and Aertsen, Abram},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2013},
pages = {681-684},
doi = {10.1007/978-3-642-40994-3_54},
url = {https://mlanthology.org/ecmlpkdd/2013/adam2013ecmlpkdd-sccql/}
}