Group decision-making processes can be supported by group recommender systems that
help groups of users obtain satisfying decision outcomes. These systems integrate a …

Abstract Rules over a Knowledge Graph (KG) capture interpretable patterns in data and
various methods for rule learning have been proposed. Since KGs are inherently …

Actionable knowledge has been qualitatively and intensively studied in the social sciences.
Its marriage with data mining is only a recent story. On the one hand, data mining has been …

Quantitative intelligence based traditional data mining is facing grand challenges from real-
world enterprise and cross-organization applications. For instance, the usual demonstration …

Structured data on customer feedback is becoming more costly and timely to collect and
organize. On the other hand, unstructured opinionated data, eg, in the form of free-text …

Action mining is a data mining method that aims to identify recommendations for changing
attribute values that can lead to the classification of data instances as examples of another …

Credit risk assessment, credit scoring and loan applications approval are one of the typical
tasks that can be performed using machine learning or data mining techniques. From this …

Customers' response is an important topic in direct marketing. This study proposes a data
mining response model supported by random forests to support the definition of target …

Action rules describe possible transitions of objects from one state to another with respect to
a distinguished attribute. Previous research on action rule discovery usually required the …

This paper introduces actionable strategies to the trisecting-and-acting three-way decision
model. We present four change-based actionable models according to action benefit and …