Text mining big data de ahmed rafeeq (18 resultados)

Condición: New.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Taschenbuch. Condición: 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. …

Condición: New.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Condición: 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.…

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 156 pp. Englisch.

Taschenbuch. Condición: 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.…

Paperback. Condición: 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.…

Paperback. Condición: new. Paperback. Questo libro presenta uno studio approfondito sul text mining mediante l'analisi dei big data, con un approccio innovativo basato sulla logica fuzzy. Poiche il volume dei dati testuali non strutturati cresce in modo esponenziale sulle piattaforme digitali, l'estrazione di conoscenze significative da set di dati su larga scala e diventata una sfida significativa. Il libro introduce metodologie avanzate che integrano i framework dei big data con la teoria degli insiemi fuzzy per affrontare l'incertezza, l'ambiguita e la vaghezza insite nelle informazioni testuali. Esplora tecniche di pre-elaborazione, estrazione di caratteristiche, analisi semantica e strategie di estrazione scalabili progettate per ambienti di dati ad alta dimensionalita. Viene proposto un modello di inferenza fuzzy per migliorare l'accuratezza della classificazione, del clustering e del processo decisionale in set di dati testuali complessi. Le valutazioni sperimentali dimostrano un miglioramento delle prestazioni rispetto ai modelli tradizionali basati su insiemi nitidi. Questo lavoro costituisce una risorsa preziosa per ricercatori, accademici e professionisti che operano nei campi della scienza dei dati, dell'intelligenza artificiale e dell'analisi dei big data, fornendo sia le basi teoriche che le implementazioni pratiche per sistemi intelligenti di estrazione di informazioni dai testi. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

Paperback. Condición: new. Paperback. Dieses Buch praesentiert eine umfassende Studie zum Text-Mining unter Verwendung von Big-Data-Analysen mit einem neuartigen, auf Fuzzy-Logik basierenden Ansatz. Da das Volumen unstrukturierter Textdaten auf digitalen Plattformen exponentiell waechst, ist die Gewinnung aussagekraeftiger Erkenntnisse aus gross angelegten Datensaetzen zu einer erheblichen Herausforderung geworden. Das Buch stellt fortgeschrittene Methoden vor, die Big-Data-Frameworks mit der Fuzzy-Mengenlehre verbinden, um Unsicherheiten, Mehrdeutigkeiten und Unschaerfen zu bewaeltigen, die textuellen Informationen innewohnen. Es untersucht Vorverarbeitungstechniken, Merkmalsextraktion, semantische Analyse und skalierbare Mining-Strategien, die fuer hochdimensionale Datenumgebungen konzipiert sind. Es wird ein Fuzzy-Inferenzmodell vorgeschlagen, um die Genauigkeit bei Klassifizierung, Clusterbildung und Entscheidungsfindung in komplexen Textdatensaetzen zu verbessern. Experimentelle Auswertungen belegen eine verbesserte Leistung im Vergleich zu herkoemmlichen, auf "crisp"-Theorie basierenden Modellen. Diese Arbeit dient als wertvolle Ressource fuer Forscher, Wissenschaftler und Praktiker in den Bereichen Datenwissenschaft, kuenstliche Intelligenz und Big-Data-Analytik und liefert sowohl theoretische Grundlagen als auch praktische Implementierungen fuer intelligente Text-Mining-Systeme. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condición: new. Paperback. Questo libro presenta uno studio approfondito sul text mining mediante l'analisi dei big data, con un approccio innovativo basato sulla logica fuzzy. Poiche il volume dei dati testuali non strutturati cresce in modo esponenziale sulle piattaforme digitali, l'estrazione di conoscenze significative da set di dati su larga scala e diventata una sfida significativa. Il libro introduce metodologie avanzate che integrano i framework dei big data con la teoria degli insiemi fuzzy per affrontare l'incertezza, l'ambiguita e la vaghezza insite nelle informazioni testuali. Esplora tecniche di pre-elaborazione, estrazione di caratteristiche, analisi semantica e strategie di estrazione scalabili progettate per ambienti di dati ad alta dimensionalita. Viene proposto un modello di inferenza fuzzy per migliorare l'accuratezza della classificazione, del clustering e del processo decisionale in set di dati testuali complessi. Le valutazioni sperimentali dimostrano un miglioramento delle prestazioni rispetto ai modelli tradizionali basati su insiemi nitidi. Questo lavoro costituisce una risorsa preziosa per ricercatori, accademici e professionisti che operano nei campi della scienza dei dati, dell'intelligenza artificiale e dell'analisi dei big data, fornendo sia le basi teoriche che le implementazioni pratiche per sistemi intelligenti di estrazione di informazioni dai testi. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. …

Taschenbuch. Condición: Neu. Text mining con i big data | Rafeeq Ahmed (u. a.) | Taschenbuch | Italienisch | 2026 | Edizioni Sapienza | EAN 9786630186628 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.…

Paperback. Condición: new. Paperback. Dieses Buch praesentiert eine umfassende Studie zum Text-Mining unter Verwendung von Big-Data-Analysen mit einem neuartigen, auf Fuzzy-Logik basierenden Ansatz. Da das Volumen unstrukturierter Textdaten auf digitalen Plattformen exponentiell waechst, ist die Gewinnung aussagekraeftiger Erkenntnisse aus gross angelegten Datensaetzen zu einer erheblichen Herausforderung geworden. Das Buch stellt fortgeschrittene Methoden vor, die Big-Data-Frameworks mit der Fuzzy-Mengenlehre verbinden, um Unsicherheiten, Mehrdeutigkeiten und Unschaerfen zu bewaeltigen, die textuellen Informationen innewohnen. Es untersucht Vorverarbeitungstechniken, Merkmalsextraktion, semantische Analyse und skalierbare Mining-Strategien, die fuer hochdimensionale Datenumgebungen konzipiert sind. Es wird ein Fuzzy-Inferenzmodell vorgeschlagen, um die Genauigkeit bei Klassifizierung, Clusterbildung und Entscheidungsfindung in komplexen Textdatensaetzen zu verbessern. Experimentelle Auswertungen belegen eine verbesserte Leistung im Vergleich zu herkoemmlichen, auf "crisp"-Theorie basierenden Modellen. Diese Arbeit dient als wertvolle Ressource fuer Forscher, Wissenschaftler und Praktiker in den Bereichen Datenwissenschaft, kuenstliche Intelligenz und Big-Data-Analytik und liefert sowohl theoretische Grundlagen als auch praktische Implementierungen fuer intelligente Text-Mining-Systeme. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Taschenbuch. Condición: Neu. Text Mining unter Verwendung von Big Data | Rafeeq Ahmed (u. a.) | Taschenbuch | 92 S. | Deutsch | 2026 | Verlag Unser Wissen | EAN 9786630176384 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.…