From big smartphone data to worldwide research: The Mobile Data Challenge
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Medical data are often scattered among multiple clinics, hospitals, insurance companies, pharmacies, and research institutions that store and process personal healthcare information. The use of information and communication technologies for health (eHealth ...
The usage of smartphones has rapidly increased during the last years. In addition to communication capabilities, they are also equipped with several sensors, and are usually carried by people throughout the day. The data collected by the means of modern sm ...
This research investigates the role of the CIO at organizational level with regard to the rise of big data and big data analytics as a potential source of innovation and competitive advantage. To this end the talk presents the results of a qualitative rese ...
Social networking sites are an increasingly important tool for career development, especially for highly skilled individuals. Moreover, they may constitute valuable sources of data for scholars and policy makers. However, little research has been conducted ...
In recent years there has been a proliferation of privately owned sensing devices such as GPS devices, cameras, home weather stations and, more importantly, smart-phones. Most of these devices are either intrinsically mobile, e.g., smart-phones and GPS dev ...
The location tracking functionality of modern mobile devices provides unprecedented opportunity to the understanding of individual mobility in daily life. Instead of studying raw geographic coordinates, we are interested in understanding human mobility pat ...
The Kamusi Project, a multilingual online dictionary website, has as one of its goals to document the lexicons of en-dangered and less-resourced languages (LRLs). Kamusi.org provides a unified platform and repository for this kind of data that is both simp ...
We present the work that allowed us to win the Next-Place Prediction task of the Nokia Mobile Data Challenge. Using data collected from the smartphones of 80 users, we explore the characteristics of their mobility traces. We then develop three families of ...
Efficiently querying data collected from Large-area Communitydriven Sensor Networks (LCSNs) is a new and challenging problem. In our previous works, we proposed adaptive techniques for learning models (e.g., statistical, non-parametric, etc.) from such dat ...
This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initiative aimed at generating innovations around smartphone-based research, as well as community-based evaluation of related mobile data analysis methodologies. Fir ...
