Accessible Knowledge-Enhanced Web Intelligence: Ontologies, Knowledge Graphs, and Natural Language Interfaces

Dear Colleagues,

Intelligent web systems increasingly rely on structured knowledge to provide accurate, explainable, and contextually appropriate responses to user needs. Ontologies and knowledge graphs enable verifiable reasoning and knowledge integration, while natural language interfaces make this intelligence accessible to diverse users. This Special Issue explores advances in knowledge-enhanced web intelligence with emphasis on accessibility, explainability, and practical deployment.

Topics of interest include

Structured Knowledge for Intelligence:

• Knowledge graphs for grounding and enhancing intelligent systems;
• Ontology-based reasoning and explainable AI;
• Knowledge integration from heterogeneous web sources;
• Hybrid approaches combining structured knowledge with machine learning.

Natural Language Knowledge Interaction:

• Conversational interfaces to structured knowledge;
• Question answering over knowledge graphs and databases;
• Natural language knowledge extraction and graph construction;
• Entity-centric and semantic information access.

Applications and Evaluation:

• Geospatial and location-based intelligent services;
• Scientific data platforms and open knowledge systems;
• Digital libraries, cultural heritage, and e-government applications;
• Accessibility evaluation and user studies;
• Case studies of real-world deployments.

Dr. Alia Abdelmoty
Dr. Usashi Chatterjee
Prof. Dr. Michael Sheng
Guest Editors

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