Call for Papers

The technical track "Semantic Technology" focuses on the topics related to Semantic Technologies and their Applications using artificial intelligence. The semantic technologies range from semantic web technologies to more advanced techniques to understand natural language using machine learning and artificial intelligence.

The focus of this track is to present research concerning issues such as 1) learning/constructing ontologies for Semantic Technology; 2) utilizing ontologies and artificial intelligence for data management, integration, and interoperability in Semantic applications; 3) architectures for achieving Semantic Technology for specific application domains; and 4) improving search techniques (or engines) with Semantic Technologies. 

This track aims to tackle research problems and practical applications for Semantic Technology. Researchers and practitioners are invited to submit papers on the theoretical, technical, and practical issues of Semantic Technology and its Applications. We are particularly interested in applying Semantic Technology to specific application domains (e.g., e-learning, e-business, social networks, geographic information systems, medical informatics, and bioinformatics).

Topics include, but are not limited to:

•  Semantic interoperability

• Ontology-enabled interoperability among e-sources

• Ontology, Taxonomy, and Folksonomy

• Schema mapping/matching and integration

• Ontology generation/learning

• Building/utilizing ontologies and knowledge bases

• Semantics and ontologies in data integration

• Ontology-enabled search (engines)

• Advanced search (engines)

• Semantic technology-enabled question answering

• Ontology-enabled information retrieval

• Semantic Technology-enabled information retrieval

• Semantic Technology-enabled Information extraction

• Data management and integration for Semantic Technology-enabled applications

• Semantic annotation

• Semantic Technology-enabled personalization

• Semantic Technology-enabled user modelling

• Semantic Technology-enabled recommendation

• Reasoning

• Semantic Technology-enabled Web/text mining

• Semantic Technology-enabled natural language understanding

• Semantic Social Network

• Semantic Social Informatics

• Recommendations via Semantic Technologies

• Semantic Knowledge Discovery

• Visual Analytics with Semantics

• Data Analytics with Semantics

• Semantics and information retrieval with deep learning

• Semantic Technology-enabled applications with deep learning

• Semantic aspects in Privacy and Security of Semantic Web Applications

• Semantic aspects in Social Network

• Semantic aspects in Geographic Information System

• Geospatial semantics

• Knowledge graph and applications

• Deep learning (or neural network) on semantics

• Deep learning (or neural network) on NLP applications

• LLM applications

• Semantic Technology using LLMs

• Language modelling in Semantic Technology

• The development and training of LLMs

•  The application of LLMs to natural language processing tasks

• The ethical and societal implications of LLMs

•  Applying Semantic Technologies to e-learning, e-business, social network, geographic information system, medical informatics, bioinformatics, and legal domains