We address the issues of discovering significant binary relationships in transaction datasets in a weighted setting. Traditional model of association rule mining is adapted to han...
Abstract. Quantitative Association Rule (QAR) mining has been recognized an influential research problem over the last decade due to the popularity of quantitative databases and th...
Spatial data mining, i.e., discovery of interesting, implicit knowledge in spatial databases, is an important task for understanding and use of spatial data- and knowledge-bases. I...
We consider the problem of finding association rules that make nearly optimal binary segmentations of huge categorical databases. The optimality of segmentation is defined by an o...
In this paper we provide a fast, data-driven solution to the failing query problem: given a query that returns an empty answer, how can one relax the query's constraints so t...