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Knowledge extraction using semantic similarity of concepts from Web of Things knowledge bases

Publication Type : Journal Article

Publisher : Data & Knowledge Engineering

Source : Data & Knowledge Engineering, Elsevier. 2021 Aug 25:101923 (Impact Factor: 1.992, SCI Indexed), Volume 135, p.101923 (2021)

Url : https://www.sciencedirect.com/science/article/pii/S0169023X21000501

Keywords : Internet of things, Interoperability, Popular concepts, Semantic Web of Things, Smart building, Smart home

Campus : Coimbatore

School : School of Engineering

Department : Computer Science

Year : 2021

Abstract : The Internet of Things (IoT) is one of the rapidly growing technologies with the aim of establishing communication among objects, people, and processes. This rapidly growing technology faces a lot of challenges that hinder its wider adoption, specifically in developing applications that involve heterogeneous domains. Currently, developing such interoperable applications require substantial efforts by the developers to hard code the requirements to ensure the correctness of transferring knowledge. The efforts can be significantly reduced by developing an interoperable platform that ensures seamless communication between heterogeneous IoT devices. W3C Web of Things (WoT) is a significant step towards enabling interoperability between IoT devices by integrating the existing Web ecosystem with “Things”. WoT provides a unified interface over a suitable network protocol facilitating interactions between different IoT protocols. WoT Thing Descriptions (TD) enrich interoperability providing both human and machine readable metadata about a Thing. However, the WoT still falls short in providing semantic interoperability due to insufficient standard vocabularies which can describe different IoT application domains. In this paper, we propose a semantic similarity-based approach to automatically identify and extract the most common concepts from sixteen popular ontologies belonging to smart home and smart building domains. The proposed method helps the developers and researchers to develop a domain ontology with reduced effort. The extracted concepts are evaluated by the domain experts and are found to be sufficient in describing the smart home and smart building domains.

Cite this Research Publication : Vamsee Muppavarapu, Dr. Gowtham R., Amelie Gyrard, and Mahda Noura, “Knowledge extraction using semantic similarity of concepts from Web of Things knowledge bases”, Data & Knowledge Engineering, Elsevier. 2021 Aug 25:101923 (Impact Factor: 1.992, SCI Indexed), vol. 135, p. 101923, 2021.

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