The Top-K Frequent Closed Itemset Mining Using Top-K SAT Problem
Abstract
In this paper, we introduce a new problem, called Top- k SAT, that consists in enumerating the Top- k models of a propositional formula. A Top- k model is defined as a model with less than k models preferred to it with respect to a preference relation. We show that Top- k SAT generalizes two well-known problems: the partial Max-SAT problem and the problem of computing minimal models. Moreover, we propose a general algorithm for Top- k SAT. Then, we give the first application of our declarative framework in data mining, namely, the problem of enumerating the Top- k frequent closed itemsets of length at least min ( ${\cal FCIM}_{min}^k$ ). Finally, to show the nice declarative aspects of our framework, we encode several other variants of ${\cal FCIM}_{min}^k$ into the Top- k SAT problem.
Cite
Text
Jabbour et al. "The Top-K Frequent Closed Itemset Mining Using Top-K SAT Problem." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2013. doi:10.1007/978-3-642-40994-3_26Markdown
[Jabbour et al. "The Top-K Frequent Closed Itemset Mining Using Top-K SAT Problem." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2013.](https://mlanthology.org/ecmlpkdd/2013/jabbour2013ecmlpkdd-topk/) doi:10.1007/978-3-642-40994-3_26BibTeX
@inproceedings{jabbour2013ecmlpkdd-topk,
title = {{The Top-K Frequent Closed Itemset Mining Using Top-K SAT Problem}},
author = {Jabbour, Saïd and Sais, Lakhdar and Salhi, Yakoub},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2013},
pages = {403-418},
doi = {10.1007/978-3-642-40994-3_26},
url = {https://mlanthology.org/ecmlpkdd/2013/jabbour2013ecmlpkdd-topk/}
}