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O2O Service Composition with Social Collaboration

Qian, Wenyi; Peng, Xin; Sun, Jun; Yu, Yijun; Nuseibeh, Bashar and Zhao, Wenyu (2017). O2O Service Composition with Social Collaboration. In: 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE 2017) (Di Penta, Massimiliano and Nyguen, Tien N. eds.), 30 October - 3 November 2017, University of Illinois at Urbana-Champaign, Illinois, USA.

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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.

Item Type: Conference or Workshop Item
Copyright Holders: 2017 ACM, 2017 IEEE
Project Funding Details:
Funded Project NameProject IDFunding Body
Adaptive Security And Privacy (XC-11-004-BN)291652EC (European Commission): FP (inc.Horizon2020 & ERC schemes)
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Interdisciplinary Research Centre: Centre for Policing Research and Learning (CPRL)
Centre for Research in Computing (CRC)
International Development & Inclusive Innovation
Item ID: 50715
Depositing User: Yijun Yu
Date Deposited: 29 Aug 2017 15:01
Last Modified: 29 Aug 2017 15:01
URI: http://oro.open.ac.uk/id/eprint/50715
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