The upsurge in the volume of unwanted emails called spam has created an intense need for
the development of more dependable and robust antispam filters. Machine learning …

Data exploration helps us understand the investigated reality in a faster and better way. In
this paper, the data to be explored are domain knowledge bases with rules representation …

Technological progress of the ever evolving world is connected with the need of developing
methods for extracting knowledge from available data, distinguishing variables that are …

Since almost all datasets may be affected by the presence of anomalies which may skew the
interpretation of data, outlier detection has become a crucial element of many datamining …

The main purpose of outlier detection algorithms is to find a new feature that is distinct from
the other features of the vector in the analyzed data set. This paper concerns outlier …

Decision support systems founded on rule‐based knowledge representation should be
equipped with rule management mechanisms. Effective exploration of new knowledge in …

The Internet and cloud-IoT technologies are an essential part of any human society
including rural societies, urban societies, smart city societies, and forthcoming societies …

This paper introduces an approach to outlier mining in the context of rule-based knowledge
bases. Rules in knowledge bases are a very specific type of data representation and it is …

In this work, two approaches of backward chaining inference implementation were
compared. The first approach uses a classical, goal-driven inference running on the client …

In this paper, a method for attribute selection is used in a dispersed decision-making system
with dynamically generated disjoint clusters. The system that is used has been proposed in …