Abstract The Internet of Things (IoT) idea, explored across the globe, brings about an
important issue: how to achieve interoperability among multiple existing (and constantly …

Full-fledged enterprise information can be a great weapon in investment analysis. However,
enterprise information is scattered in different databases and websites. The information from …

Ontology matching aims at identifying the correspondences between instances and data
properties of different ontologies. The use of data mining approach in matching ontology …

Six datasets have been published under the title of Billion Triple Challenge (BTC) since
2008. Each such dataset contains billions of triples extracted from millions of documents …

Abstract Domain knowledge graphs, which compose scattered information about domain
entities, are expressive when organizing information for enterprise systems in the decision …

Efficient decision-making in earthquake emergencies plays a crucial role in ensuring
individual safety, protecting personal property, and maintaining societal stability. However …

This paper investigates the semantic modeling of smart cities and proposes two ontology
matching frameworks, called Clustering for Ontology Matching‐based Instances (COMI) and …

Entity resolution (ER) aims to identify whether two entities in an ER task refer to the same
real-world thing. Crowd ER uses humans, in addition to machine algorithms, to obtain the …

Semantic similarity is a broad term used to describe many tools, models and methods
applied in knowledge bases, semantic graphs, text disambiguation, ontology matching and …

This paper is devoted to investigating if it is possible to update stale alignments, based
solely on the analysis of changes introduced to ontologies participating in the alignment. A …