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Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/10910

Title: Mapping for activity recognition in the context-aware systems using software sensors
Authors: Pathan, Kamran Taj
Reiff-Marganiec, Stephan
Hong, Yi
Issue Date: Dec-2011
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Citation: Proceedings - IEEE 9th International Conference on Dependable, Autonomic and Secure Computing, DASC 2011, 2011, pp. 215-221
Abstract: Context-aware systems are concerned with identifying the context of a user and then to either provide that information based on queries or to automatically decide on appropriate actions to be taken. Some context aspects (such as location) are easy to sense through hardware, while the activity of a user has shown to be somewhat elusive to being sensed with hardware sensors. As users use web services more frequently they are exchanging messages with the services through the SOAP protocol. SOAP messages contain data, which is valuable if gathered and interpreted right - especially as this data can be shedding information on the activity of a user that goes beyond "sitting at the computer and typing". We have developed software sensors, essentially based on monitoring SOAP messages and inserting data for further reasoning and querying into a semantic context model. In this paper we consider a solution to map the data from a SOAP message to our OWL ontology model automatically. Specifically, we explain the methodology to map from SOAP messages to an existing structure of knowledge.
DOI Link: 10.1109/DASC.2011.56
ISBN: 978-1-4673-0006-3
Links: http://hdl.handle.net/2381/10910
http://ieeexplore.ieee.org/xpl/articleDetails(...)
Version: Post-print
Status: Peer-reviewed
Type: Conference Paper
Rights: Copyright © 2011 IEEE. Deposited with reference to the publisher's archiving policy available on the SHERPA/RoMEO website. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Appears in Collections:Conference Papers & Presentations, Dept. of Computer Science

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