Name
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.
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Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/ASE.2017.8115657 | ASE |
Keywords | Field | DocType |
O2O service composition,social collaboration,customer services,offline route planning,service selection,concrete composite service,optimal collaboration plan,Markov chain Monte Carlo algorithm,model checking,timed automata,online-to-offline coomerce,optimal combination | Data mining,Model checking,Markov chain Monte Carlo,Computer science,Automaton,Quality of service,Theoretical computer science,Online and offline,Time constraint,Social collaboration,Distributed computing,Scalability | Conference |
ISSN | ISBN | Citations |
1527-1366 | 978-1-5386-2684-9 | 2 |
PageRank | References | Authors |
0.36 | 21 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wenyi Qian | 1 | 24 | 2.83 |
| Xin Peng | 2 | 599 | 67.59 |
| Jun Sun | 3 | 1407 | 120.35 |
| Yijun Yu | 4 | 1558 | 113.40 |
| Bashar Nuseibeh | 5 | 4201 | 347.16 |
| Wenyun Zhao | 6 | 526 | 54.45 |