Application of Semantic Technologies in Intelligent Environment
A special issue of Big Data and Cognitive Computing (ISSN 2504-2289).
Deadline for manuscript submissions: 31 May 2025 | Viewed by 664
Special Issue Editors
Interests: knowledge representation and engineering; semantic technologies; machine learning; digital libraries
Interests: NLP; big data and data analytics; applications of artificial intelligence for smart society
Interests: machine learning; deep learning; computer vision; robotics; medical imaging
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
It is our pleasure to announce a new Special Issue of Big Data and Cognitive Computing titled “Application of Semantic Technologies in Intelligent Environment”.
Semantic technology is a set of knowledge modeling methods, standards and tools that help intelligent agents to understand language and process information in a way similar to how humans do. Semantic technologies can automatically store, manage and retrieve information based on its meaning and logical relationships. They provide advanced means for categorizing and processing data, as well as for discovering relationships within various data sets.
The primary goal of semantic technologies is to help computers understand data and thereby to facilitate the reuse of information and provide semantic interoperability between heterogeneous information systems.
Semantic technologies are “meaning-centered”. They involve a lot of generic applications, such as the encoding and decoding of semantic representation; the automatic recognition of topics and concepts; semantic annotation and the semantic enhancement of data sets; semantic data integration; information and meaning extraction; semantic search, etc. To enable the encoding of meaning with the data, appropriate technologies include RDF/RDFS and OWL, which rely on embedded semantics and provide convenient tools for describing ontologies. Embedded semantics of data offers significant advantages, such as reasoning on data and extracting concepts and associations between concepts in text.
The widespread penetration of large language models has made the task of their integration with modern semantic technologies particularly relevant in order to obtain a maximum synergistic effect. We hope that this Special Issue will contribute in that direction.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:
- Ontology engineering and ontology mediation;
- Linked data and their applications;
- Automatic metadata extraction;
- Automatic generation of knowledge graphs from texts;
- Semantic search;
- Semantic interoperability of information systems;
- Semantic enhancement of big data;
- Big data semantics, search and mining;
- Integrating large language models and knowledge graphs;
- Semantic technologies for intelligent urban environment;
- Semantic technologies in eHealth;
- Semantic technologies for intelligent agriculture;
- Semantic technologies for finance and administration;
- Semantic technologies in education;
- Semantic technologies in the energy sector.
We look forward to receiving your contributions.
Prof. Dr. Maria Nisheva-Pavlova
Prof. Dr. Galia Angelova
Dr. Moulay A. Akhloufi
Guest Editors
Manuscript Submission Information
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Keywords
- semantic web
- linked data
- knowledge graph
- ontology
- big data
- information retrieval
- semantic interoperability
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