By Guojun Wang, Yanbo Han, Gregorio Martínez Pérez
This booklet constitutes the refereed complaints of the tenth Asia-Pacific providers Computing convention, APSCC 2016, held in Zhangjiajie, China, in November 2016.
The 38 revised complete papers offered during this ebook have been conscientiously reviewed and chosen from 107 submissions. The papers disguise a variety of themes within the fields of cloud/utility/Web computing/big facts; foundations of providers computing; social/peer-to-peer/mobile/ubiquitous/pervasive computing; service-centric computing versions; integration of telecommunication SOA and net companies; company technique integration and administration; and defense in services.
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Additional resources for Advances in Services Computing: 10th Asia-Pacific Services Computing Conference, APSCC 2016, Zhangjiajie, China, November 16-18, 2016, Proceedings
So the process of getting appropriate service compositions can be transformed into getting service compositions from different granularity layers. Through experimental analysis, we can demonstrate that this model can provide users with different granularity service compositions which meet the multiple granularity demands of users. And can also decrease the response time of service composition at the same time. Keywords: Service computing Á recommendation Á Granular computing Service composition Á Services granular space Á Service 1 Introduction With the development of new concepts of service computing such as pervasive computing and cloud computing, applications and data were available to the users in the form of Web services(or network interfaces), the concept of Services Computing came into being.
Clustering by means of medoids. In: Dodge, Y. ) Statistical Data Analysis Based on the L1–Norm and Related Methods, pp. 405–416. North-Holland (1987) 6. : K-means v/s K-medoids: a comparative study. In: Proceedings of National Conference on Recent Trends in Engineering & Technology, vol. 13 (2011) 7. : Similarity index based on local paths for link prediction of complex networks. Phys. Rev. E 80(4), 046122 (2009) 8. : Predicting missing links via local information. Eur. Phys. J. B Condens. Matter Complex Syst.
How to discover and choose the appropriate APIs to compose for users’ requirement is critical . For another, only a few APIs were ever used by the users and the reuse rate of most services is rather low . How to improve the usage rate of the existing APIs is also an important issue. In order to solve the two problems mentioned above, we propose a multi-relation based manifold ranking algorithm to assist Mashup developers discovering a list of suitable APIs. Firstly, we cluster existing Mashups into groups according to their textual descriptions so that the Mashups within a cluster are similar in functionality.