A trust-based approach to selection of business services

Li, Sufen; Fan, Yushun; Li, Xitong

doi:10.1080/0951192x.2011.574235

Cited by 11 publications

(7 citation statements)

References 18 publications

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“…In the future, some empirical data specific from the manufacturing sectors such as the well-known clothing manufacturing ecosystem in Ningbo (Li, Fan, and Li 2011) or the Boeing Company which consists of 13,000 + professional service suppliers in more than 100 countries (Huang et al 2011) will be collected and used to improve the effectiveness of domain-aware reputable recommendation method. Also as the MSE is not static but evolving over time, how to take the evolution mechanism into account may be helpful to improve the performance.…”

Section: Resultsmentioning

confidence: 99%

“…A performance evaluation method for service-oriented manufacturing network, which combines performance indicators on business, service and implementation level, is proposed for the optimal service selection and composition in the MSE (Huang et al 2011). Li et al introduce a method to calculate the trust among services and then the trust-based multi-service selection method is presented to select the optimal services for the composition (Li, Fan, and Li 2011). The conceptual pro-active service ecosystem framework is introduced to study the three-layerlogical architecture and the five temporal phase composition process in the MSE (Cardoso and Camarinha-Matos 2013).…”

Section: Related Workmentioning

confidence: 99%

“…The services with higher reputation will have a higher usability and credibility. Thus the reputation-based trust (Nepal, Malik, and Bouguettaya 2011) plays a major role in conducting business collaboration over the Internet in service-oriented environments (Ridha, Rizvi, and Azzedin 2007;Li, Fan, and Li 2011). Some works aggregate the opinions of other users in the trust network to generate personalised recommendation for consumers based on graph-based trust models, interaction-based trust models and hybrid trust models (Yao et al 2011;Wang and Vassileva 2007;Sherchan, Nepal, and Paris 2013;Wu et al 2013).…”

Section: Introductionmentioning

confidence: 99%

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Domain-aware reputable service recommendation in heterogeneous manufacturing service ecosystem

Fan

Huang

Tan

et al. 2014

International Journal of Computer Integrated Manufacturing

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Networked manufacturing becomes an important manufacturing method for modern manufacturing enterprises. With the wide adoption of service-oriented architecture and cloud manufacturing, manufacturing enterprises and organisations publish their manufacturing capability, such as resources, processes and knowledge as manufacturing services. A rapidly growing manufacturing service ecosystem can be observed nowadays, which brings the information overload problem for the service selection. Thus, how to organise these services and how to recommend the reputable services become two important issues for the manufacturing service retrieval and reuse. In this paper, the service cluster method WSTPCluster, which develops the topic model based on Latent Dirichlet Allocation, is employed to cluster services into specific domains. As the service ecosystem can be modelled as a heterogeneous service network, a unified reputation propagation method URPM is proposed to calculate the reputation of services and to distinguish the reputable services in each domain. Combining WSTPCluster and URPM, domain-aware reputable service recommendation method is introduced to recommend the high reputable services in each domain for the consumers. Experiments show that this method brings a better performance both in the recommendation accuracy and in the long tail recommendation.

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Section: Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Domain-aware reputable service recommendation in heterogeneous manufacturing service ecosystem

Fan

Huang

Tan

et al. 2014

International Journal of Computer Integrated Manufacturing

Self Cite

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“…1) Reduced Location Distance: Comparing BSE with TBM, service provider is less sensitive to location distance, as online platform provides an extensive mechanism to communicate; comparing BSE with web service, in web service, location affects the transmission rate of service, while in BSE, it affects the transportation cost [10].…”

Section: B Key Features Of Bsementioning

confidence: 99%

“…3) Sensitive Trust and Security: As open and dynamic characteristics of BSE [11], consumers become more sensitive to trust and security, they need to balance the risk and convenience [10,12].…”

Section: B Key Features Of Bsementioning

confidence: 99%

Complex Network-Oriented Analysis on Business Service Ecosystem

Luo

Fan

2013

2013 International Conference on Service Sciences (ICSS)

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Service-oriented approach has changed the pattern of providing products and services in business area. Through supply chain on the online platform, many business entities (consumers and providers) can now make business transactions in a more extensive and convenient way. As huge business entities and their complex correlations exist and evolve continuously, this system is regarded as Business Service Ecosystem (BSE). It is critical to discern BSE's topology structure and evolution rule, to support its management. In this paper, first, business correlation model and key features of BSE are investigated; then, a Complex Network-oriented Analysis Framework (CNOAF) is proposed, which aims to solve the above problem, and a Time-based Correlation Bipartite Graph is established as the core model to deal with correlation; finally, an empirical study of marine logistic service indicates the effectiveness of CNOAF, and several valuable insights are obtained for its development.

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