Welcome to MobDM 2016

Many high velocity applications deal with data of changing characteristics. For instance, managing objects that move in space has applications in traffic control, law enforcement, homeland security, urban planning. Using another example, a distinguishing trait that sets high velocity apart from disk-stored data is that high velocity data usually exhibits time-changing data characteristics. As most decision-making tasks rely on the recency of their supporting data, the evolving nature of the data creates tremendous complexity for many mobile data mining algorithms. On the other hand, users are often interested in changes embodied by the data. Therefore, how to make mining algorithms more effective and efficient in view of changing data characteristics has become a major challenge in a wide range of mobile data mining application domains.

This workshop solicits papers on stream mining of high velocity data. It welcomes domain-driven applications in Web, science, engineering, healthcare, finance, business, transportation, and telecommunication. We also encourage position and on-going research papers.



The use of autonomous UAVs to improve pesticide application in crop fields

André C. P. L. F. de Carvalho

Big Data Stream Mining

Albert Bifet

INESC TEC - Laboratório Associado