O2O service composition with social collaboration

Wenyi Qian, Xin Peng, Jun Sun, Yijun Yu, Bashar Nuseibeh, Wenyun Zhao

Full text DOI 10.1109/ase.2017.8115657 dblp

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.

BibTeX

@inproceedings{Qian-al:ASE17,
  author    = {Wenyi Qian and
               Xin Peng and
               Jun Sun and
               Yijun Yu and
               Bashar Nuseibeh and
               Wenyun Zhao},
  title     = {{O2O} service composition with social collaboration},
  booktitle = {ASE},
  pages     = {451--461},
  publisher = {{IEEE} Computer Society},
  year      = {2017},
}

O2O service composition with social collaboration

Abstract

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