A Hybrid Social Network-based Collaborative Filtering Method for Personalized Manufacturing Service Recommendation

Abstract

Nowadays, social network-based collaborative filtering (CF) methods are widely applied to recommend suitable products to consumers by combining trust relationships and similarities in the preference ratings among past users. However, these types of methods are rarely used for recommending manufacturing services. Hence, this study has developed a hybrid social network-based CF method for recommending personalized manufacturing services. The trustworthy enterprises and three types of similar enterprises with different features were considered as the four influential components for calculating predicted ratings of candidate services. The stochastic approach for link structure analysis (SALSA) was adopted to select top K trustworthy enterprises while also considering their reputation propagation on enterprise social network. The predicted ratings of candidate services were computed by using an extended user-based CF method where the particle swarm optimization (PSO) algorithm was leveraged to optimize the weights of the four components, thus making service recommendation more objective. Finally, an evaluation experiment illustrated that the proposed method is more accurate than the traditional user-based CF method.

Research on cloud manufacturing service recommendation based on graph neural network

“…For example, Fan et al [ 13 ] conducted service recommendation research from the perspective of manufacturing service clustering, developed a service clustering method by using a Latent Dirichlet Allocation-based topic model to cluster CMfg services into specific domains, and then introduced a domain-aware reputation service recommendation method to recommend highly reputable services in each domain for users. Zhang et al [ 41 ] developed a CF method based on hybrid social networks for recommending personalized manufacturing services. Hao et al [ 42 ] found that most of the traditional recommendation methods ignore the evolutionary characteristics of CMfg service systems, and for this problem, a time-aware target reconfiguration service description method was proposed, leading to a new recommendation strategy for manufacturing services.…”

A Data Warehouse-Based System for Service Customization Recommendations in Product-Service Systems

“…Influential related work efforts have utilized RSs to assist customers in identifying the manufacturing services (e.g., resources, capabilities) needed to accomplish the required manufacturing task [ 29 , 30 , 31 , 32 , 33 , 34 ].…”

“…Some authors have used a hybrid recommendation method that integrates social network and collaborative filtering techniques to recommend manufacturing services [ 29 , 30 ]. By adopting collaborative filtering and social network techniques, the authors in [ 29 ] predicted the missing Quality of Services (QoS) values of manufacturing services.…”

“…Finally, the top-k manufacturing services with the highest QoS values are recommended to service consumers. While in [ 30 ], the authors utilized a Stochastic Approach for Link Structure Analysis (SALSA) to base their hybrid approach for recommending manufacturing services. SALSA was employed to select the top trustworthy enterprises.…”