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O2O service composition with social collaboration

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Show simple item record Qian, Wenyi Peng, Xin Sun, Jun Yu, Yijun Nuseibeh, Bashar Zhao, Wenyun 2018-04-26T08:04:39Z 2018-04-26T08:04:39Z 2017
dc.description peer-reviewed en_US
dc.description.abstract In Online-to-Offline (O2O) commerce, customer services may need to be composed from online and offline services. Such composition is challenging, as it requires effective selection of appropriate services that, in turn, support optimal combination of both online and offline services. In this paper, we address this challenge by proposing an approach to O2O service composition which combines offline route planning and social collaboration to optimize service selection. We frame general O2O service composition problems using timed automata and propose an optimization procedure that incorporates: (1) a Markov Chain Monte Carlo (MCMC) algorithm to stochastically select a concrete composite service, and (2) a model checking approach to searching for an optimal collaboration plan with the lowest cost given certain time constraint. Our procedure has been evaluated using the simulation of a rich scenario on effectiveness and scalability. en_US
dc.language.iso eng en_US
dc.publisher Association for Computing Machinery en_US
dc.relation.ispartofseries 32 IEEE/ACM International Conference on Automated Software Engineering (ASE);pp. 451-461
dc.rights © ACM, 2017. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in 32 IEEE/ACM International Conference on Automated Software Engineering (ASE), pp. 451-461, en_US
dc.subject collaboration en_US
dc.subject concrete en_US
dc.subject libraries en_US
dc.subject printing en_US
dc.subject optimization en_US
dc.subject quality of service en_US
dc.subject planning en_US
dc.title O2O service composition with social collaboration en_US
dc.type info:eu-repo/semantics/conferenceObject en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.identifier.doi 10.1109/ASE.2017.8115657
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US

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