In this paper, we propose four data mining models for the Internet of Things, which are multi-
layer data mining model, distributed data mining model, Grid based data mining model and …

The problem addressed in this paper is the challenge of automated construction of
knowledge discovery workflows, given the types of inputs and the required outputs of the …

The DataMiningGrid system has been designed to meet the requirements of modern and
distributed data mining scenarios. Based on the Globus Toolkit and other open technology …

Introduction Computer science applications are becoming more and more network centric,
ubiquitous, knowledge intensive, and computing demanding. This trend will result soon in …

Data analysis techniques and services are needed to mine the massive amount of data
available and to extract useful knowledge from it. e service-oriented architecture (SOA) is …

As computerization in healthcare services increase, the amount of available digital data is
growing at an unprecedented rate and as a result healthcare organizations are much more …

Link prediction is a central task in the field of dynamic complex network analysis. A major
trend in this area consists of applying a dyadic topological approach. Most of existing …

Power management has become one of the main challenges for data center infrastructures.
Currently, the cost of powering a server is approaching the cost of the server hardware itself …

Data mining techniques are used in many application areas to extract useful knowledge
from large datasets. Very often, parameter sweeping is used in data mining applications to …

Distributed data mining implements techniques for analyzing data on distributed computing
systems by exploiting data distribution and parallel algorithms. The grid is a computing …