This is the first part of a large survey paper in which we analyze recent literature on Formal
Concept Analysis (FCA) and some closely related disciplines using FCA. We collected 1072 …

Traditional association rule mining based on the support–confidence framework provides
the objective measure of the rules that are of interest to users. However, it does not reflect …

Abstract Mining High Utility Itemsets (HUIs) is an important task with many applications.
However, the set of HUIs can be very large, which makes HUI mining algorithms suffer from …

Many techniques for cleaning dirty data are based on enforcing some set of integrity
constraints. Conditional functional dependencies (CFDs) are a combination of traditional …

Methods for cleaning dirty data typically employ additional information about the data such
as user-provided constraints specifying when data is dirty, eg, domain restrictions, illegal …

This work can be seen as a contribution to the area of social network analysis. By
considering Formal Concept Analysis (FCA) as the underlying formalizing tool, we use logic …

Pattern mining is one of the most studied fields in data mining. Being mostly motivated by
practitioners, pattern mining algorithms are often based on heuristics and are lacking …

Malware often uses packing, an obfuscation strategy, to bypass antivirus. Identifying and
understanding packers is therefore essential for analyzing suspicious binary files. Proposed …

Rare itemsets are important sort of patterns that have a wide range of practical applications,
in particular, in analysis of biomedical data. Although mining rare patterns poses specific …

Prostate cancer is one of the leading causes of death in men. Accurate segmentation of
prostate magnetic resonance imagery allows for the maximum volume of the prostate to be …