Guest editorial: Special issue on “current topics of knowledge graphs and semantic web”

Knowledge Graphs are considered as a set of data points associated with relations to describe the domains such as an organization, business or academics. They have a potential role to bridge the semantic gap between unstructured and structured information and fostered new research directions, tasks with new possibilities to represent, query, visualize, interact and make more understandable information. Knowledge Graphs are powerful to representing data in search and recommendation systems that explored new insights about the domain. Recently, Knowledge Graphs gain popularity with deep learning and graph embedding. This special issue has been organized to invite the extended version of KGSWC-2021 conference accepted papers. The primary aim of this issue:

• to provide a forum for the Semantic Web community, bringing together researchers and practitioners in industry to share ideas about R and D projects; and

• to increase the adoption of the Semantic Web technologies within the region.

• Deep Learning on Knowledge Graphs.

• Graph-based Data Science.

• Text Mining and Natural Language Processing.

• Combining Semantic Graphs with Property Graphs.

• Probabilistic Knowledge Graphs.

• Vocabularies, Schemas and Ontologies.

• Web Analytics.

• Knowledge Mining and Fusion.

• Security and Data Privacy with Semantic Technologies.

• Knowledge Graphs and Deep Semantics.

• Semantic Linking and Search.

• Machine Learning in Semantic Computing.

• Linked Data.

• Reasoning.

• Social Web and Web Science.

• Mobile Web, Sensors and Semantic Streams.

• Services, APIs, Processes and Cloud Computing.

• Benchmarking and Empirical Evaluation.

This special issue invited only selected papers of KGSWC-2021 conference to extend. We have followed the journal guidelines to accomplish the review process and finally accepted 12 papers.

The selected papers are on many different topics, such as process mining application on patient waiting time (Dogan, 2022); maintenance of RDB2RDF in enterprise knowledge graphs (Vidal et al., 2022); deep neural network-based approach for fake news detection (Katariya et al., 2022); ranking community detection algorithms for complex social networks (Rani and Kumar, 2022); agglomerative clustering enhanced GA for optimal seed selection (Mehta, 2022); CNN-BERT for measuring agreement (Harly and Girsang, 2022); hotel room personalization via ontology and rule-based reasoning (Ojino et al., 2022); fake news detection on Twitter [¹]; semiautomated process for generating knowledge graphs (Keshan et al., 2022); From ontology to knowledge graph with agile methods (DeBellis and Dutta, 2022); keyword-based faceted search interface for Knowledge Graph construction and exploration (Sellami and Zarour, 2022); and finally, applied personal profile ontology for personnel appraisals (Usip et al., 2022).