Download Advances in Services Computing: 10th Asia-Pacific Services by Guojun Wang, Yanbo Han, Gregorio Martínez Pérez PDF

By Guojun Wang, Yanbo Han, Gregorio Martínez Pérez

This publication constitutes the refereed court cases of the tenth Asia-Pacific companies Computing convention, APSCC 2016, held in Zhangjiajie, China, in November 2016.

The 38 revised complete papers awarded during this e-book have been rigorously reviewed and chosen from 107 submissions. The papers hide quite a lot of subject matters within the fields of cloud/utility/Web computing/big information; foundations of prone computing; social/peer-to-peer/mobile/ubiquitous/pervasive computing; service-centric computing types; integration of telecommunication SOA and internet providers; enterprise technique integration and administration; and safety in services.

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Extra resources for Advances in Services Computing: 10th Asia-Pacific Services Computing Conference, APSCC 2016, Zhangjiajie, China, November 16-18, 2016, Proceedings

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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. 71(4), 623–630 (2009) 9. : Clustering through ranking on manifolds. In: Proceedings of the 22nd International Conference on Machine Learning, pp. 73–80. ACM (2005) 10. : Efficient manifold ranking for image retrieval. In: Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp.

It can automatically balance the prestige and the diversity of the top ranked vertices in a principled way. Tong et al. [17] proposed a goodness measure for a given top-K ranking list. It can capture both the relevance and the diversity for a given ranking list. Zhou et al. [18] proposed a unified neighborhood random walk distance measure called ServiceRank, which integrates various types of links and vertex attributes by a local optimal weight assignment to tightly integrate ranking and clustering by mutually and simultaneously enhancing each other.

7(4), 586–598 (2014) 4. : An empirical study of ProgrammableWeb: a network analysis on a Service-Mashup system. In: Proceedings of IEEE 19th International Conference on Web Services (ICWS), Honolulu, HI, pp. 552–559 (2012) 5. : 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.

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