منابع مشابه
Inferring Stop-Locations from WiFi.
Human mobility patterns are inherently complex. In terms of understanding these patterns, the process of converting raw data into series of stop-locations and transitions is an important first step which greatly reduces the volume of data, thus simplifying the subsequent analyses. Previous research into the mobility of individuals has focused on inferring 'stop locations' (places of stationarit...
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Automatic event location extraction from text plays a crucial role in many applications such as infectious disease surveillance and natural disaster monitoring. The fundamental limitation of previous work such as SpaceEval is the limited scope of extraction, targeting only at locations that are explicitly stated in a syntactic structure. This leads to missing a lot of implicit information infer...
متن کاملInferring the Social-Connectedness of Locations from Mobility Data
An often discriminating feature of a location is its social character or how well its visitors know each other. In this paper, we address the question of how we can infer the social contentedness of a location by observing the presence of mobile entities in it. We study a large number of mobility features that can be extracted from visits to a location. We use these features for predicting the ...
متن کاملInferring the Everyday Task Capabilities of Locations
People rapidly learn the capabilities of a new location, without observing every service and product. Instead they map a few observations to familiar clusters of capabilities. This paper proposes a similar approach to computer discovery of routine location capabilities, applying machine learning to predict unobserved capabilities based on a combination of a small body of local observations and ...
متن کاملYour WiFi Is Leaking: Inferring Private User Information Despite Encryption
This thesis describes how wireless networks can inadvertently leak and broadcast users’ personal information despite the correct use of encryption. Users would likely assume that their activities (for example, the program or app they are using) and personal information (including age, religion, sexuality and gender) would remain confidential when using an encrypted network. However, we demonstr...
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ژورنال
عنوان ژورنال: PLOS ONE
سال: 2016
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0149105