Fuzzy-Logic-Based Approaches for Knowledge Management and User Modelling

Dear Colleagues,

Fuzzy logic is a computational intelligence method that was introduced by Lotfi A. Zadeh. It allows for the representation of vague and imprecise data with linguistic terms, making it an ideal approach for handling the uncertainty and vagueness that exist in both everyday scenarios and diverse scientific areas. Incorporating fuzzy logic into systems enables them to reason in a human-like way. In recent years, the increased interest in artificial intelligence and in developing smart systems that imitate human thinking and behavior have prompted the extensive use of fuzzy logic.

This Special Issue aims to explore the latest advancements and applications of fuzzy-logic in knowledge management and user modeling. It seeks to advance the understanding and application of fuzzy logic in these domains, shedding light on its potential to address challenges such as information overload, data ambiguity, and user behavior understanding and prediction. Particularly, this Special issue aims to inspire further research in innovative methodologies for tackling the complexities inherent in managing knowledge resources, and for handling and capturing the nuanced and subjective nature of user preferences, interests, and interactions. It delves into various applications of fuzzy logic in knowledge management, showcasing how it enables more nuanced reasoning and decision-making processes in the face of incomplete or ambiguous information, and into the diverse applications of fuzzy logic in user modeling, highlighting its role in personalization, recommendation systems, and adaptive interfaces. Therefore, this Special Issue seeks to provide insights into the current innovations, state-of-the-art methodologies, challenges, and future directions in the fields of knowledge management and the development more responsive, adaptable and context-aware user models. 

The topics of interest include (but are not limited to) the following:

• Fuzzy logic in expert systems
• Fuzzy logic-based knowledge representation models
• Fuzzy systems for information retrieval and recommendation
• Fuzzy logic in decision support systems
• Fuzzy clustering and classification techniques
• Fuzzy-logic-based semantic web and ontology engineering
• Integration of fuzzy logic with other AI techniques for enhanced knowledge management
• Fuzzy-logic-based personalized recommendation systems
• Fuzzy-logic-based user modelling
• Fuzzy-logic-based adaptive user interfaces
• Fuzzy-logic-based user behavior prediction
• Fuzzy-logic-based emotion recognition in user modelling

Dr. Konstantina Chrysafiadi
Dr. Dionisios Sotiropoulos
Guest Editors

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