Combining Global and Local Trust for Service Recommendation


Recommending trusted services to users is of paramount value in service-oriented environments. Reputation has been widely used to measure the trustworthiness of services, and various reputation models for service recommendation have been proposed. Reputation is basically a global trust score obtained by aggregating trust from a community of users, which could be conflicting with an individual's personal opinion on the service. Evaluating a service's trustworthiness locally based on the evaluating user's own or his/her friends' experiences is sometimes more accurate. However, local trust assessment may fail to work when no trust path from an evaluating user to a target service exists. This paper proposes a hybrid trust-aware service recommendation method for service-oriented environment with social networks via combining global trust and local trust evaluation. A global trust metric and a local trust metric are firstly presented, and then a strategy for combining them to predict the final trust of service is proposed. To evaluate the proposed method's performance, we conducted several simulations based on a synthesized dataset. The simulation results show that our proposed method outperforms the other methods in service recommendation.

Meeting Name

2014 21st IEEE International Conference on Web Services (2014: Jun. 27-Jul. 2, Anchorage, AK)


Computer Science

Keywords and Phrases

Information services; Social networking (online); Reputation; Reputation models; Service recommendations; Service-oriented environment; Target services; Trust; Trust assessments; Trust evaluation; Web services

International Standard Book Number (ISBN)


Document Type

Article - Conference proceedings

Document Version


File Type





© 2014 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Jun 2014