Intelligent Technologies for Scientific Research and Engineering

S. Kannadhasan

• Publisher: Bentham Science Publishers
• Year: 2026
• Topic: Computer Science
• eBook ISBN:
  9798898815318
• Subtopic: Artificial Intelligence (AI) & Semantics
• Index: Computer Science

Advanced Technologies for Science and Engineering - Vol. 4 is a comprehensive compilation of cutting-edge research at the intersection of artificial intelligence, data analytics, and advanced engineering applications. The book focuses on leveraging intelligent technologies to solve complex, real-world problems in today's data-driven landscape.
 
Comprising thirty-seven peer-reviewed chapters, the volume blends theoretical foundations with practical implementations across diverse domains such as healthcare informatics, smart grids, energy forecasting, remote sensing, recommender systems, and climate modelling. It highlights innovative models, optimisation techniques, and scalable frameworks, supported by real-world case studies from industries including telecommunications, banking, e-commerce, and social media.
 
Key Features
 
Extensive coverage of AI, machine learning, deep learning, and big data analytics
 
 
46 peer-reviewed chapters combining theory with real-world applications
 
 
Multidisciplinary topics, including healthcare, energy, climate science, and smart systems
 
 
Focus on hybrid models, optimisation methods, and scalable frameworks
 
 
Emphasis on contemporary challenges such as data privacy, sustainability, and intelligent automation

Table of contents

• Welcome
• Table of Content
• Title
• BENTHAM SCIENCE PUBLISHERS LTD.
• Preface
• List of Contributors
• A Study of Big Data Techniques for Extracting Valuable Information
• Adaptive Recommendation Systems for Improved Information Analysis
• An Assessment of Big Data Analysis Technologies for Improved Information Delivery
• Analyzing the Effectiveness of Big Data Tools for Analyzing Complex Data Structures
• Automated Reasoning and Topic Detection in Text Clustering
• Automated Reasoning Tools and their Application in Text Mining
• Hybrid Intelligence for Information Analysis for Machine Learning and Automated Reasoning
• Performance Analysis of Rule-Based Reasoning in Complex Data Environments
• Evaluating the Usefulness of Big Data in Decision Making
• Evaluating the Role of Data Mining in Enhancing Decision-Making
• Harnessing Big Data for Advanced Business Intelligence
• Examining the Role of Big Data in Advanced Statistical Modeling
• Exploiting User Preferences through Content-based Recommendation Systems
• Exploring the Application of Data Mining in the Detection of Fraudulent Transactions
• Leveraging Text Mining Techniques for Efficient Information Discovery
• Exploring the Potential of Big Data for Monetization of Information
• Exploring the Potential of Data Visualization to Enhance Data Analysis
• Exploring the Potential of Recommender Systems for Semantic Analysis
• Text Mining for Intelligent Information Analysis for Opportunities and Challenges
• Bridging Logic and Data to Automated Reasoning for Big Data Analysis
• Investigating the Benefits of Text Mining for Information Analysis
• Data-driven Strategies for Resource Optimization Using Data Mining
• Investigating the Role of Data Mining in Enhancing Business Performance
• Learning Features and Preferences with Matrix Factorization Models for Recommendation Systems
• Leveraging Big Data to Enhance the Analysis and Use of Information
• Leveraging Text Mining Techniques for Automated Information Analysis
• Optimizing Recommendations in Real-Time with Hybrid Recommendation Systems
• Proactive Automated Reasoning Systems for Spatial and Temporal Data Analysis
• Proving Knowledge Bases for Automated Reasoning for Information Analysis
• Social Network Analysis for Movie Recommendations and Information Extraction
• Text Mining Approaches for Next-Level Information Analysis and Decision Support
• Text Mining for Automated Data Analysis and Information Retrieval
• Text Mining for Effective Information Extraction and Analysis
• Enhancing Information Processing and Analysis with Text Mining
• Text Mining Approaches to Enhance Knowledge Discovery and Information Analysis
• Advantages and Limitations of Big Data Analysis Tools
• Utilizing Contextual Recommendation Systems for Advanced Comprehension of Information