In recent years, the problem of association rule mining in transactional data has been well studied. We propose to extend the discovery of classical association rules to the discovery of association rules of conjunctive queries in arbitrary relational data, inspired by the Warmr algorithm, developed by Dehaspe and Toivonen, that discovers association rules over a limited set of conjunctive quer...

Discovering hidden patterns in large sets of workforce schedules to gain insight into the potential knowledge in workforce schedules are crucial to better understanding the workforce dispatching decision making process, thereby improve workforce allocation and optimization. In this paper, a conceptual framework of the scheduling pattern discovery system is proposed. Association rule extraction ...

The paper describes a knowledge discovery platform and a novel process for finding association rules based on the algorithm FP-Growth and its variants. Built software solution has been optimized in terms of memory usage and computation time as well as the impact of all modifications made to the whole process of rules discovery The process of rule discovery is illustrated on a real database cont...

Declarative rules, such as functional dependencies, are widely used for cleaning data. Several systems take them as input for detecting errors and computing a “clean” version of the data. To support domain experts,in specifying these rules, several tools have been proposed to profile the data and mine rules. However, existing discovery techniques have traditionally ignored the time dimension. R...