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S-BRAIN #42: Social and Sensor Data Fusion in the Cloud

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dc.contributor.author Saltarin, J.
dc.date.accessioned 2016-11-04T16:08:07Z
dc.date.available 2016-11-04T16:08:07Z
dc.date.issued May
dc.date.issued 2013
dc.identifier.citation S-BRAIN Series 2012/2013
dc.identifier.uri http://copelabs.ulusofona.pt/index.php/events-5/events/details/340-sbrain-meeting-42-jonnahtan-saltarin-siti-ulht
dc.identifier.uri http://siti2.ulusofona.pt:8085/xmlui/handle/123456789/557
dc.description.abstract In this S-BRAIN we will explore the potential of fusing social and sensor data in the cloud, presenting an application —a travel recommendation system— that predicts how the mood of people is likely to be on where and when users wish to travel. The system blends the heterogeneous social and sensor data for integrated analysis, extracting weather-dependent people’s mood information from Twitter and meteorological sensor data streams. In order to handle massively streaming data, the system employs various cloud-serving systems, such as Hadoop, HBase, and
dc.title S-BRAIN #42: Social and Sensor Data Fusion in the Cloud


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