Domain-aware reputable service recommendation in heterogeneous manufacturing service ecosystem

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. 1. Introduction With the rapid evolution of the computer and network technologies, as well as the pressing need of international competitiveness in manufacturing era over these years, networked manufacturing (Fan and Huang 2007) has become an important pattern for the collaboration among modern manufacturing enterprises and organisations. Considering the advantage of the service-oriented architecture (SOA) for collaboration, manufacturing enterprises and organisations are trying to publish their manufacturing capability as modern manufacturing services over the Internet (Jang et al. 2008). These manufacturing services – including manufacturing message specification services for the communication between different manufacturing enterprises (Wu, Xi, and Zhou 2008), production system controlling and monitoring services to support reconfiguration of the manufacturing lifecycles and the intelligent function-alities, and machining simulation services for the cross-platform and high-level numerical control simulation (Karnouskos et al. 2010; Phaithoonbuathong et al. 2010) – have been introduced for the collaboration among suppliers and customers over the Internet (Cai, Zhang, and Zhang 2011). Hence manufacturing enterprises can focus on their