Cryptocurrencies gain trust in users by publicly disclosing the full creation and transaction history. In return, history faithfully records whole spectrum of cryptocurrency user behaviors. This article analyzes summarizes existing research on knowledge discovery transactions using data mining techniques. Specifically, we classify into three aspects, i.e., tracings blockchain address linking, a...

Performance modeling has long been considered a difficult science requiring expertise from seasoned capacity planners. Currently there has been a shift in the area of performance modeling towards ease-of-use and automation of the entire process. Automation not only hides this difficult science from the users but also delivers immediate Return on Investment for administrators with deploy and run...

In the last few decades, Grid technologies have emerged as an important area in parallel and distributed computing. The Grid can be seen as a computational and large-scale support, and even in some cases as a high-performance support. In recent years, the data mining community have been increasingly using Grid facilities to store, share, manage and mine large-scale data-driven applications. Ind...

Todate visualization has not been extensively harnessed in knowledge discovery in databases (KDD). In this paper, we show that a multidimensional visualization (MDV) technique can be used synergistically with a machine learning program like C4.5 to uncover new knowledge. Used together, the two approaches span the KDD spectrum between complete automation on one hand and fully manual on the other...

Trajectory data play a fundamental role to an increasing number of applications, such as transportation management, urban planning and tourism. Trajectory data are normally available as sample points. However, for many applications, meaningful patterns cannot be extracted from sample points without considering the background geographic information. In this paper we propose a novel framework for...