DocumentCode
2212677
Title
Towards a Mobile Health Context Prediction: Sequential Pattern Mining in Multiple Streams
Author
Hassani, Marwan ; Seidl, Thomas
Author_Institution
Data Manage., RWTH Aachen Univ., Aachen, Germany
Volume
2
fYear
2011
fDate
6-9 June 2011
Firstpage
55
Lastpage
57
Abstract
Context prediction is an emerging topic in the fields of data mining and information management which is both promising and challenging. Predicting the location of mobile objects was a frequently tackled subtask of mobile context prediction in recent researches. For scenarios of managing health information of mobile persons, the prediction of near future health status of persons is at least equally important to predicting their location. We introduce in this paper, to the best of our knowledge, a first method for predicting a next health context of mobile persons equipped with body sensors and a mobile device. The suggested Prefix Span-based method searches for sequential patterns within multiple streaming inputs from the body sensors as well as other contextual streams that influence the health context. We discuss additionally the implementation of our method in an energy aware mobile-server environment.
Keywords
data mining; health care; information management; mobile computing; pattern recognition; data mining; health information; information management; mobile device; mobile health context prediction; mobile objects; mobile server environment; multiple streams; prefix span based method; sequential pattern mining; Context; Data mining; Mobile communication; Performance evaluation; Prediction algorithms; Sensors; Servers; Data mining; health context; mobile context prediction; multiple streams mining; sequential pattern mining;
fLanguage
English
Publisher
ieee
Conference_Titel
Mobile Data Management (MDM), 2011 12th IEEE International Conference on
Conference_Location
Lulea
Print_ISBN
978-1-4577-0581-6
Electronic_ISBN
978-0-7695-4436-6
Type
conf
DOI
10.1109/MDM.2011.28
Filename
6068495
Link To Document