Perspectives of Human Mobility in Location-based Social Networks: Models and Applications
- Day - Time: 07 June 2013, h.11:00
- Place: Area della Ricerca CNR di Pisa - Room: C-29
Speakers
- Anastasios Noulas (Cambridge University)
Referent
Abstract
In this talk I will be sharing my experience of mining, analysing and modeling user mobility in location-based social networks in the past couple of years. We will initially present an agent based modeling approach that captures fundamental properties of human urban movement in 34 metropolitan cities. The work that is based on a dataset comprised of millions of Foursquare user check-ins will shed light on the role of geography and the spatial density of settlements in human mobility. Subsequently, we will consider two different mobile application scenarios. First we will formulate a mobile recommendation task where the goal is to accurately new places a user will visit in future time periods. We shall see how a random walk on a graph that connects users with places can offer good recommendations in an extremely sparse data context. Next, we shall formulate an even more challenging problem where we try to predict the next check-in of a user in real time. Exploiting a supervised learning approach that employs synchronously multiple layers of mobility data, we will show that accurate predictions of user whereabouts can be attained if models are trained appropriately. Finally, we will discuss on the feedback loop between abstract models and applications and how mutual benefits emerge in two seemingly distant areas of research in human mobility.
Biografia: Anastasios Noulas is a PhD candidate in the Computer Laboratory at Cambridge University. He holds an MEng in Computer Science (2009) from University College London. His research interests are focused on the analysis and modelling of human movement and geographic social networks, with techniques that span the areas of Complex Systems, Data Mining and applied Machine Learning. In 2012 he joined Telefonica Research in Spain for a research fellowship participating in a project on Smart Cities that exploited Call Detail Records and data sourced from location-based services to infer activities in urban environments. As of 2013 he has joined the EPSRC project GALE that aims to the development of the next generation of mobile recommender systems and urban neighbourhood modelling for the provision of local knowledge to remote visitors of an area. More details are available http://www.cl.cam.ac.uk/~an346/