This paper presents an active learning approach to the problem of systematic noise inference and noise elimination, specifically the inference of Associated Corruption (AC) rules...
Popular data mining methods support knowledge discovery from patterns that hold in binary relations. We study the generalization of association rule mining within arbitrary n-ary ...
Efficient mining of frequent patterns from large databases has been an active area of research since it is the most expensive step in association rules mining. In this paper, we pr...
Background: Unsupervised annotation of proteins by software pipelines suffers from very high error rates. Spurious functional assignments are usually caused by unwarranted homolog...
Irena I. Artamonova, Goar Frishman, Dmitrij Frishm...
Mining of frequent closed itemsets has been shown to be more efficient than mining frequent itemsets for generating non-redundant association rules. The task is challenging in data...