Augmentation of contextual knowledge based on domain dominant words for IoT applications interoperability

Semantic web technology is adapted to the internet of things (IoT) for webbased applications to globally connect the services. Web ontology language (OWL) domain ontology is a powerful machine-readable language for domain knowledge representation. The developer stored the IoT application relevant ontology in a repository or catalogue. Hence, IoT applicationrelated ontology files are available for reuse, but many of the IoT application-relevant ontology files are publicly not available or inaccessible. The proposed idea is to extract the contextual knowledge of IoT applications that contain inaccessible ontology files. The context-wise specific domain IoT applications are not obtainable, hence respective ontology-based research papers are identified and their frequent terms are computed. The selected contextual dominant frequent terms from the transport domain are passed into the skip-gram flavour of word2vector modelled natural language processing (NLP) corpus which produces most similar terms. The domain experts select the appropriate terms to annotate in OWL ontology for contextual knowledge augmentation. Finally, 1422 contextual terms were generated based on dominant terms of selected IoT applications.