Ontologies have gained a lot of popularity and recognition in the semantic web because of
their extensive use in Internet-based applications. Ontologies are often considered a fine …

Purpose This study aims to propose a collaborative knowledge-based ontological research
model for designing a collaborative product development process (PDP) while considering …

Recently, IoT has greatly influenced our daily lives through various applications. One of the
most promising application is smart city that leverages IoT devices to manage cities without …

With the continuous advancement of methods, tools, and techniques in ontology
development, ontologies have emerged in various fields such as machine learning, robotics …

Cloud is a multitenant architecture that allows the cloud users to share the resources via
servers and is used in various applications, including data classification. Data classification …

Feature Ensembles are a robust and effective method for finding the feature set that yields
the best predictive accuracy for learning agents. However, current feature ensemble …

Abstract Cloud of Things (CoT) emerges as a pivotal paradigm, connecting Internet of
Things (IoT) devices to the Cloud Computing space, facilitating the efficient management of …

A real-life hierarchical classification system is developed to automatically extract a domain
ontology from repair data collected during the warranty period of an original equipment …

Lack of methodologies for ontology quality evaluation causes a challenge in producing good
quality ontologies. Thus, we developed an iterative quality methodology to address this gap …

Noise addition is a data distortion technique widely used in data intensive applications. For
example, in machine learning tasks it helps to reduce overfitting, whereas in data privacy …