Learning Urban Nightlife Routines from Mobile Data
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As we live our daily lives, our surroundings know about it. Our surroundings consist of people, but also our electronic devices. Our mobile phones, for example, continuously sense our movements and interactions. This socio-geographic data could be continuo ...
EPFL2011
Tasks that rely on semantic content of documents, notably Information Retrieval and Document Classification, can benefit from a good account of document context, i.e. the semantic association between documents. To this effect, the scheme of latent semantic ...
EPFL2010
In this thesis, we address the analysis of activities from long term data logs with an emphasis on video recordings. Starting from simple words from video, we progressively build methods to infer higher level scene semantics. The main strategies used to ac ...
We describe a failure of standard extremal models to account for a catastrophic rainfall event in the coastal regions of Venezuela on 14-16 December 1999, due both to inaccurate tail modelling and to an inadequate treatment of clusters of rare events. We i ...
Background: Alcohol consumption is causally linked to nonadherence to antiretroviral treatment that in turn causes an increase in HIV/AIDS mortality. This article presents a method to calculate the percentage of HIV/AIDS deaths attributable to alcohol cons ...
This paper addresses the task of mining typical behavioral patterns from small group face-to-face interactions and linking them to social-psychological group variables. Towards this goal, we define group speaking and looking cues by aggregating automatical ...
In this work we address the problem of modeling varying time duration sequences for large-scale human routine discovery from cellphone sensor data using a multi-level approach to probabilistic topic models. We use an unsupervised learning approach that dis ...
In this work we discover the daily location-driven routines which are contained in a massive real-life human dataset collected by mobile phones. Our goal is the discovery and analysis of human routines which characterize both individual and group behaviors ...
Alcohol is one of the most commonly consumed drugs in the world. While the effects of alcohol on cognitive and psychomotor skills have been well studied, little research has examined alcohol's effects on visual processing. In the present study, we evaluate ...
The automatic discovery of group conversational behavior is a relevant problem in social computing. In this paper, we present an approach to address this problem by defining a novel group descriptor called bag of group-nonverbal-patterns defined on brief o ...