Advanced Information Retrieval System: Theoretical and Experimental Perspective

Urmila Pilania, Manoj Kumar, Sanjay Singh

• Publisher: Bentham Science Publishers
• Year: 2026
• eBook ISBN: 9798898813666
• Topic: Computer Science
• Subtopic: Information Technology
• Index: Computer Science

Advanced Information Retrieval System: Theoretical and Experimental Perspective blends foundational theory with practicality to provide an integrative exploration of modern information retrieval (IR) systems. This volume examines a wide range of IR methodologies, from classical indexing and ranking techniques to cutting-edge AI-driven approaches, demonstrating how these systems can be applied across diverse domains, including web search, recommendation systems, sentiment analysis, and multimedia retrieval.

The book takes a structured approach towards guiding readers from traditional IR models to advanced, hybrid frameworks. The early chapters focus on classical and modern retrieval techniques with comparative analyses of different methods. Subsequent chapters focus on applied scenarios such as tourism recommender systems, sentiment mining from YouTube comments, book and medicine recommendation engines, and image-audio-based retrieval systems. Advanced topics include semantic role classification using BERT, hybrid filtering methods, personalised web crawlers, and experimental studies on smoothing techniques. Real-world case studies and experimental evaluations illustrate how theoretical models translate into effective, domain-specific IR applications.

Key Features
Comprehensive coverage of traditional, modern, and hybrid IR techniques

Practical frameworks for recommendation systems, sentiment analysis, and web crawling

Integration of AI and machine learning methods, including BERT and TF-IDF models

Experimental evaluations and comparative analyses across multiple domains

Real-world applications spanning tourism, healthcare, fashion, and multimedia retrieval

Table of contents

• Table of Content
• Welcome
• Title
• BENTHAM SCIENCE PUBLISHERS LTD.
• FOREWORD
• Preface
• Evaluating Traditional and Modern Information Retrieval Techniques
• Comparative Analysis of Different Information Retrieval Methods
• Comparative Analysis of Collaborative and Content Filtering Techniques on Web-Scraped Data for a Tourism Recommender System
• An Information Retrieval-Based Framework for Analysing Viewer Sentiments in YouTube Comments
• A Framework for Sentiment Mining in YouTube Comments Using Information Retrieval Methods
• Sentence Interpretation and Semantic Role Classification Using BERT
• Image-Audio Based Recommendations System for Information Retrieval
• Hybrid Book Recommendation System Integrating Collaborative and Content-Based Filtering Techniques
• Medicine Recommendation System using TF-IDF and Machine Learning
• Image-Based Recommendation System for Various Fashion Styles
• Personalized Web Crawler for Retrieving Patent and Research Paper Information from Google Patents and IEEE Xplore
• REFERENCES