Advanced Information Retrieval System by Urmila Pilania (.ePUB)+
File Size: 59.0 MB
Advanced Information Retrieval System: Theoretical and Experimental Perspective by Urmila Pilania, Manoj Kumar, Sanjay Singh
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Overview: 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 initial four to five chapters of the proposed book provide a theoretical understanding and comprehensive review of IR techniques. The subsequent chapters will then transition to more advanced techniques, such as Artificial Intelligence (AI), Deep Learning, and data mining, for applicability in real-life chapters. Theory without experimental results is incomplete, so the authors have added a significant portion to support the experimental perspective. This book encompasses both theoretical and practical approaches in relation to real-world applications. The book will cover the latest methods in AI, big data, data mining, multimedia retrieval, and personalization. What makes this book different is its systematic presentation, including foundational areas like indexing, ranking algorithms, query processing, relevance feedback, and evaluation metrics, as well as newer topics like semantic retrieval, integration of Machine Learning techniques, and user behavior modeling. Not only does it foster learning, but it also encourages innovation, which has served as a great foundation for academic research and system development. Target Readership: Graduate students, researchers, academics and professionals in Computer Science, information retrieval, Data Science, AI, and Machine Learning.
Genre: Non-Fiction > Tech & Devices
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