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奥克兰理工大学喻坚教授学术报告会通知

阅读量:10 发布时间:2018-11-08 09:18:18

时间:2018年11月12日 下午4:00-5:30

地点:第一教学楼3楼会议室

主持人:喻坚,奥克兰理工大学副教授

Title: Constructing and Evaluating an Evolving Web-API Network for Service Discovery

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Dr Jian Yu is an Assoc. Professor in Department of Computer Science, Auckland University of Technology and Adjunct Professor at North China University of Technology. He holds a PhD degree in Computer Software and Theory from Peking University. Dr Yu’s main research interests are Service-Oriented Computing, Ubiquitous Computing, and Complex Networks. He is on the programme committee of major international conferences in service-oriented computing area including ICSOC, IEEE SCC, IEEE APSCC and IEEE SOCA. He has over 90 publications and has published in top journals such as ACM CSUR, IEEE TSC and TITS, and Elsevier IS and JCSS. Dr Yu has organized four special issues on Context-Aware Services and related topics for journals such as PUC and have organized over ten international conferences and workshops.

 Abstract: Web-APIs enable cross-organizational functionality integration over the Web and thus are the foundation of modern distributed service-based systems. However, despite the rapid increase in the number of Web-APIs available on the Internet, the discovery and uptake of appropriate Web-APIs by businesses on a Web scale is still a great challenge. One of the main reasons is that Web-APIs registered on directories such as ProgrammableWeb.com are in general isolated, as they are registered by diverse providers independently and progressively. In this paper, we present a method for analyzing the Web-API ecosystem and propose a complex-network-based approach for building an evolving social network for Web APIs. We conduct our analysis in two phases: First, from the complex network perspective, we investigate mashups and Web-APIs interactions and analyze the Web-API popularity distribution using the popular ProgrammbleWeb dataset. Second, we quantitatively measure the Preferential Attachment mechanism which is a key driver of an evolving network. Based on our analysis, we propose an approach to construct an evolving Web-API social network based on the theoretical procedure of the Barabási-Albert complex network model. Results presented in this work will not only provide insight into the topology of the Web-API ecosystems but also serve as a practical guide for designing an evolving-network-based solution for service discovery and recommendation.