Estimating web service reputation from integrated social service network model

Kyung Ryul Kim, Jooik Jung, Sejin Chun, Gunhee Cho, Kyong Ho Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Social networks facilitate information sharing and communication among people who have common interests. Although social networks have been widely used to compute the reputations of Web services, they are limited in the ability to support the sophisticated estimation of service reputations. This paper proposes a sophisticated method of computing service reputations, which considers service requesters, raters and providers participating in the service ecosystem. In order to represent the interactions among the service participants, we also propose an integrated model which combines social and service network models. Based on the model, the proposed method calculates the credibility and expertise of the raters and providers of a service and applies them to the reputation of the service. Experimental results with real-world Web services show that the proposed method computes service reputations elaborately.

Original languageEnglish
Title of host publicationProceedings - 2013 19th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2013
PublisherIEEE Computer Society
Pages510-515
Number of pages6
ISBN (Print)9781479920815
DOIs
Publication statusPublished - 2013
Event2013 19th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2013 - Seoul, Korea, Republic of
Duration: 2013 Dec 152013 Dec 18

Publication series

NameProceedings of the International Conference on Parallel and Distributed Systems - ICPADS
ISSN (Print)1521-9097

Other

Other2013 19th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2013
Country/TerritoryKorea, Republic of
CitySeoul
Period13/12/1513/12/18

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture

Fingerprint

Dive into the research topics of 'Estimating web service reputation from integrated social service network model'. Together they form a unique fingerprint.

Cite this