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Inhaltsangabe
This book presents a comprehensive study on text mining using big data analytics with a novel fuzzy logic-based approach. As the volume of unstructured textual data grows exponentially across digital platforms, extracting meaningful knowledge from large-scale datasets has become a significant challenge. The book introduces advanced methodologies that integrate big data frameworks with fuzzy set theory to address uncertainty, ambiguity, and vagueness inherent in textual information. It explores preprocessing techniques, feature extraction, semantic analysis, and scalable mining strategies designed for high-dimensional data environments. A fuzzy inference model is proposed to enhance classification, clustering, and decision-making accuracy in complex text datasets. Experimental evaluations demonstrate improved performance compared to traditional crisp-based models. This work serves as a valuable resource for researchers, academicians, and practitioners working in data science, artificial intelligence, and big data analytics, providing both theoretical foundations and practical implementations for intelligent text mining systems.
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Über die Autorin bzw. den Autor
Dr. Rafeeq AhmedAcademician and researcher in the field of Artificial Intelligence, Machine Learning, and Big Data Analytics. He has extensive teaching and research experience and has published several research papers in reputed journals and conferences. His research interests include text mining, explainable AI, and intelligent data-driven.
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Text Mining using Big Data (Paperback)
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Paperback. Zustand: new. Paperback. This book presents a comprehensive study on text mining using big data analytics with a novel fuzzy logic-based approach. As the volume of unstructured textual data grows exponentially across digital platforms, extracting meaningful knowledge from large-scale datasets has become a significant challenge. The book introduces advanced methodologies that integrate big data frameworks with fuzzy set theory to address uncertainty, ambiguity, and vagueness inherent in textual information. It explores preprocessing techniques, feature extraction, semantic analysis, and scalable mining strategies designed for high-dimensional data environments. A fuzzy inference model is proposed to enhance classification, clustering, and decision-making accuracy in complex text datasets. Experimental evaluations demonstrate improved performance compared to traditional crisp-based models. This work serves as a valuable resource for researchers, academicians, and practitioners working in data science, artificial intelligence, and big data analytics, providing both theoretical foundations and practical implementations for intelligent text mining systems. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9786209795305
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Text Mining using Big Data
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Text Mining using Big Data
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Text Mining using Big Data
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents a comprehensive study on text mining using big data analytics with a novel fuzzy logic-based approach. As the volume of unstructured textual data grows exponentially across digital platforms, extracting meaningful knowledge from large-scale datasets has become a significant challenge. The book introduces advanced methodologies that integrate big data frameworks with fuzzy set theory to address uncertainty, ambiguity, and vagueness inherent in textual information. It explores preprocessing techniques, feature extraction, semantic analysis, and scalable mining strategies designed for high-dimensional data environments. A fuzzy inference model is proposed to enhance classification, clustering, and decision-making accuracy in complex text datasets. Experimental evaluations demonstrate improved performance compared to traditional crisp-based models. This work serves as a valuable resource for researchers, academicians, and practitioners working in data science, artificial intelligence, and big data analytics, providing both theoretical foundations and practical implementations for intelligent text mining systems. Bestandsnummer des Verkäufers 9786209795305
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Text Mining using Big Data
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Taschenbuch. Zustand: Neu. Text Mining using Big Data | Rafeeq Ahmed (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786209795305 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 134944643
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Text Mining using Big Data
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents a comprehensive study on text mining using big data analytics with a novel fuzzy logic-based approach. As the volume of unstructured textual data grows exponentially across digital platforms, extracting meaningful knowledge from large-scale datasets has become a significant challenge. The book introduces advanced methodologies that integrate big data frameworks with fuzzy set theory to address uncertainty, ambiguity, and vagueness inherent in textual information. It explores preprocessing techniques, feature extraction, semantic analysis, and scalable mining strategies designed for high-dimensional data environments. A fuzzy inference model is proposed to enhance classification, clustering, and decision-making accuracy in complex text datasets. Experimental evaluations demonstrate improved performance compared to traditional crisp-based models. This work serves as a valuable resource for researchers, academicians, and practitioners working in data science, artificial intelligence, and big data analytics, providing both theoretical foundations and practical implementations for intelligent text mining systems.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 156 pp. Englisch. Bestandsnummer des Verkäufers 9786209795305
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Text Mining using Big Data (Paperback)
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LAP Lambert Academic Publishing, 2026
ISBN 10: 6209795307
ISBN 13: 9786209795305
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Paperback. Zustand: new. Paperback. This book presents a comprehensive study on text mining using big data analytics with a novel fuzzy logic-based approach. As the volume of unstructured textual data grows exponentially across digital platforms, extracting meaningful knowledge from large-scale datasets has become a significant challenge. The book introduces advanced methodologies that integrate big data frameworks with fuzzy set theory to address uncertainty, ambiguity, and vagueness inherent in textual information. It explores preprocessing techniques, feature extraction, semantic analysis, and scalable mining strategies designed for high-dimensional data environments. A fuzzy inference model is proposed to enhance classification, clustering, and decision-making accuracy in complex text datasets. Experimental evaluations demonstrate improved performance compared to traditional crisp-based models. This work serves as a valuable resource for researchers, academicians, and practitioners working in data science, artificial intelligence, and big data analytics, providing both theoretical foundations and practical implementations for intelligent text mining systems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9786209795305
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