A comparative media-bias pipeline on 37 news outlets using hierarchical topics, sentiment, entities, and LLM ontologies was tested, with clear signals from titles and entities but failures in body sentiment and larger ontology comparisons.
Ontologies in Digital Twins: A Systematic Literature Review
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abstract
Digital Twins (DT) facilitate monitoring and reasoning processes in cyber-physical systems. They have progressively gained popularity over the past years because of intense research activity and industrial advancements. Cognitive Twins is a novel concept, recently coined to refer to the involvement of Semantic Web technology in DTs. Recent studies address the relevance of ontologies and knowledge graphs in the context of DTs, in terms of knowledge representation, interoperability and automatic reasoning. However, there is no comprehensive analysis of how semantic technologies, and specifically ontologies, are utilized within DTs. This Systematic Literature Review (SLR) is based on the analysis of 82 research articles, that either propose or benefit from ontologies with respect to DT. The paper uses different analysis perspectives, including a structural analysis based on a reference DT architecture, and an application-specific analysis to specifically address the different domains, such as Manufacturing and Infrastructure. The review also identifies open issues and possible research directions on the usage of ontologies and knowledge graphs in DTs.
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cs.AI 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
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Unraveling Media Perspectives: A Comprehensive Methodology Combining Large Language Models, Topic Modeling, Sentiment Analysis, and Ontology Learning to Analyse Media Bias
A comparative media-bias pipeline on 37 news outlets using hierarchical topics, sentiment, entities, and LLM ontologies was tested, with clear signals from titles and entities but failures in body sentiment and larger ontology comparisons.