In this article, we review the state‐of‐the‐art techniques in mining data streams for mobile and ubiquitous environments. We start the review with a concise background of data stream …
In today's competitive market, companies need to use discovery knowledge techniques to make better, more informed decisions. But these techniques are out of the reach of most …
The conventional technologies and methods are not able to store and analyse recent data that come from different sources: various devices, sensors, networks, transactional …
As the size of available datasets has grown from Megabytes to Gigabytes and now into Terabytes, machine learning algorithms and computing infrastructures have continuously …
D Talia, P Trunfio - Communications of the ACM, 2010 - dl.acm.org
Introduction Computer science applications are becoming more and more network centric, ubiquitous, knowledge intensive, and computing demanding. This trend will result soon in …
Data mining (DM) is increasingly used in the analysis of data generated in life sciences, including biological data produced in several disciplines such as genomics and proteomics …
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 …
M Pujari, R Kanawati - 2012 IEEE 24th International …, 2012 - ieeexplore.ieee.org
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 …
Security requirements analysis depends on how well-trained analysts perceive security risk, understand the impact of various vulnerabilities, and mitigate threats. When systems are …