A review of data mining ontologies | Emerald Insight Books and journals Case studies Expert
Briefings Open Access Publish with us Advanced search A review of data mining ontologies …

This paper presents a distributed architecture for automating data mining (DM) processes
using standard languages. DM is a difficult task that relies on an exploratory and analytic …

Data mining is a science guided by experimentation. Still, there exists only limited support to
automate such experimentation, making it a laborious and error-prone process. In this …

Data Mining has reached a quite mature and sophisticated stage, with a plethora of
techniques to deal with complex data analysis tasks. In contrast, the capability of users to …

Today's intelligent data assistants (IDA) for data analysis are focusing on how to do effective
and intelligent data analysis. However this is not a trivial task since one must take into …

Abstract Machine learning and analytical techniques are increasingly becoming an integral
part of many types of information systems. Despite the hype around these technologies …

The treatment of complex systems often requires the manipulation of vague, imprecise and
uncertain information. Indeed, the human being is competent in handling of such systems in …

In Artificial Intelligence, planning refers to an area of research that proposes to develop
systems that can automatically generate a result set, in the form of an integrated decision …

In this paper, we describe a practical and effective approach to incorporating goal-based
reasoning into ontology-driven applications. We present a reusable ontology-driven …

The rapid growth of databases in last years asks organizations to deal with issues related to
the management of large amounts of data, which represent a valuable resource for decision …