Discovery and Analysis About the Evolution of Service Composition Patterns
Keywords:Topic evolution graph, service composition recommendation, topic model
Service ecosystems, consisting of various kinds of services and mashups, usually keep evolving over time. Existing works on the evolution of service ecosystems focus on either evaluating the impacts of single services’ changes on the usage of services and the stability of the whole ecosystem, or discovering co-occurrence relationship between services, but fail to disclose any knowledge from the aspect of the evolution of service composition patterns. Based on our previous work, this paper moves one step further, revealing the latent service composition trends in a service ecosystem and providing more distinct explanation of different topic evolution patterns. A novel methodology, named Extended Dependency-Compensated Service Co-occurrence LDA (EDC-SeCo-LDA), is developed to calculate the directed dependencies between different topics and build topic evolution graph. The evolution trend of service composition could be disclosed by the graph intuitively. What’s more, EDC-SeCo-LDA proposes five different ways to adopt dependency compensation to improve the performance when making service recommendation. Experiments on ProgrammableWeb.com show that EDC-SeCo-LDA can reveal significant topic dependencies, and recommend service composition more effectively, i.e., 6% better in terms of Mean Average Precision compared with baseline approaches.
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