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AuthorAamir, Tooba
AuthorBouguettaya, Athman
AuthorDong, Hai
AuthorMistry, Sajib
AuthorErradi, Abdelkarim
Available date2023-04-10T09:10:03Z
Publication Date2017
Publication NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ResourceScopus
URIhttp://dx.doi.org/10.1007/978-3-319-69035-3_3
URIhttp://hdl.handle.net/10576/41796
AbstractWe propose a new social-sensor cloud services selection framework for scene reconstruction. The proposed research represents social media data streams, i.e., images' metadata and related posted information, as social sensor cloud services. The functional and non-functional aspects of social sensor cloud services are abstracted from images' metadata and related posted information. The proposed framework is a 4-stage algorithm, to select social-sensor cloud services based on the user queries. The selection algorithm is based on spatio-temporal indexing, spatio-temporal and textual correlations, and quality of services. Analytical results are presented to prove the efficiency of the proposed approach in comparison to a traditional approach of image processing. Springer International Publishing AG 2017.
SponsorAcknowledgement. This research was made possible by DP160103595 grant from Australian Research Council and NPRP 9-224-1-049 grant from the Qatar National Research Fund (a member of The Qatar Foundation). The statements made herein are solely the responsibility of the authors.
Languageen
PublisherSpringer Verlag
Subjectsocial-sensor
cloud services
social media data streams
metadata
TitleSocial-sensor cloud service for scene reconstruction
TypeConference Paper
Pagination37-52
Volume Number10601 LNCS
dc.accessType Abstract Only


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