Soft Computing for Web Intelligence

This text explores a diverse range of soft computing approaches applied to web personalization, including fuzzy logic, neutrosophy, and evolutionary computation. It provides insight into the customization of content, recommendations, and user interfaces to create personalized and engaging web experiences. It examines the integration of soft computing approaches in clustering similar users and items, discovering user preferences, and developing web intelligent systems. The text:Presents analysis and exploration of data processing techniques and their importance in designing web intelligent systems. Discusses the applications of different soft computing approaches like fuzzy logic, neutrosophy, machine learning in data processing and designing intelligent systems. Showcases recent developments in feature selection and extractions from numerical data, textual, and multimodal data. Explains soft computing methods to create cutting-edge optimization algorithms, and examines different soft computing techniques and fuzzy multiple-criteria decision-making in the context of web intelligent systems and data analytics. Highlights frameworks, use cases, and examples that illustrate the practical applications of soft computing in developing intelligent web systems and applications. It is written for senior undergraduate students, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.