Unsupervised User Similarity Mining in GSM Sensor Networks
نویسندگان
چکیده
منابع مشابه
Unsupervised User Similarity Mining in GSM Sensor Networks
Mobility data has attracted the researchers for the past few years because of its rich context and spatiotemporal nature, where this information can be used for potential applications like early warning system, route prediction, traffic management, advertisement, social networking, and community finding. All the mentioned applications are based on mobility profile building and user trend analys...
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In pervasive environments, users are situated in rich context and can interact with their surroundings through various services. To improve user experience in such environments, it is essential to find the services that satisfies user preferences in certain context. Thus the suitability of discovered services is highly dependent on how much the context-aware system can understand users’ current...
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Online social networks like Instagram are places for communication. Also, these media produce rich metadata which are useful for further analysis in many fields including health and cognitive science. Many researchers are using these metadata like hashtags, images, etc. to detect patterns of user activities. However, there are several serious ambiguities like how much reliable are these informa...
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Article history: Received 17 May 2011 Received in revised form 28 January 2013 Accepted 23 February 2013 Available online 4 March 2013
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The development of positioning systems and wireless connectivity has made it possible to collect users’ fine-grained movement data. This availability of movement data can be applied in a broad range of services. In this paper, we present a novel tool for calculating users’ similarity based on their movements. This tool, MinUS, integrates the technologies of trajectory pattern mining with the st...
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ژورنال
عنوان ژورنال: The Scientific World Journal
سال: 2013
ISSN: 1537-744X
DOI: 10.1155/2013/589610