Advances in Intelligent Data and Information Processing : Proceedings of the International Conference on Intelligent Data and Information Processing (IDIP2025), Volume 2 / / edited by Witold Pedrycz, John Wang, Kuo-Kun Tseng, Xilong Qu

• Autore: Pedrycz Witold
• Pubblicazione: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2026
• Edizione: 1st ed. 2026.
• Descrizione fisica: 1 online resource (418 pages)
• Disciplina: 620.00285
• Soggetto topico: Engineering - Data processing; Computational intelligence; Artificial intelligence; Data Engineering; Computational Intelligence; Artificial Intelligence
• Nota di contenuto: -- Application of Fused Neural Network Model in English Sentiment Analysis -- Research on Prediction of Housing Security Demand Based on Big Data and its Impact on Policy Making -- Deep Learning Model Optimization for Natural Language Processing -- Early Warning Model Construction of Enterprise Financial Crisis Based on Random Forest Algorithm, etc.
• Sommario/riassunto: This book integrates practical engineering insights with cutting-edge AI/ML methodologies to address real-world intelligent data processing challenges, prioritizing actionable solutions over theoretical abstraction. By bridging algorithmic foundations with industry-specific use cases, it equips readers to translate technical concepts into deployable systems efficiently. Unlike traditional texts that silo theory and practice, this approach embeds hands-on implementation frameworks, including data preprocessing pipelines, model optimization techniques, and scalability strategies, directly within contextualized problem-solving scenarios. Covering core topics from edge AI deployment to large-scale data analytics, it spans both foundational principles and emerging trends like federated learning and real-time processing. Tailored for IT professionals, computer science practitioners, and engineering researchers, it also serves as a valuable resource for graduate students specializing in data science or intelligent systems. Ideal for upskilling, project reference, or curriculum supplementation, it empowers readers to tackle complex data-intensive tasks with confidence in academic, corporate, or R&D settings.
• Titolo autorizzato: Advances in Intelligent Data and Information Processing
• ISBN: 3-032-16702-7
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9911066010503321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Networks and Systems, . 2367-3389 ; ; 1808