A Hybrid Semantic Matchmaker for IoT Services

The use of semantic Web technologies and service oriented computing paradigm in Internet of Things research has recently received significant attention to create a semantic service layer that supports virtualisation of and interaction among "Things". Using service-based solutions will produce a deluge of services that provide access to different data and capabilities exposed by different resources. The heterogeneity of the resources and their service attributes, and dynamicity of mobile environments require efficient solutions that can discover services and match them to the data and capability requirements of different users. Semantic service matchmaking process is the fundamental construct for providing higher level service-oriented functionalities such as service recommendation, composition, and provisioning in Internet of Things. However, scalability of the current approaches in dealing with large number of services and efficiency of logical inference mechanisms in processing huge number of heterogeneous service attributes and metadata are limited. We propose a hybrid semantic service matchmaking method that combines our previous work on probabilistic service matchmaking using latent semantic analysis with a weighted-link analysis based on logical signature matching. The hybrid method can overcome most cases of semantic synonymy in semantic service description which usually presents the biggest challenge for semantic service matchmakers. The results show that the proposed method performs better than existing solutions in terms of precision (P@n) and normalised discounted cumulative gain (NDCG(n)) measurement values.