Ahmed rafeeq (42 risultati)

Condizione: New.

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

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

Taschenbuch. Condizione: 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. …

Condizione: New.

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

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

Condizione: New.

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

Hardcover. Condizione: Very Good. No Dustjacket. First Edition. ISBN . B002BJEA2W Hardback. No Dustjacket. First Edition from 1993 as stated on the copyright page. Tight sound unmarked copy in Very Good condition. No Signature.

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

7 Bl. Titelei, 439 S., mit 301 Bildern, 11 Tab. u. 243 Literaturstellen, OKart., geringe Gebrauchs- u. Stellspuren, ausgeschied. Bibl.-Expl. mit den üblichen Kennzeichnungen. ISBN 3816911900.

Condizione: New.

Condizione: New.

Condizione: New.

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

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

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

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

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

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

Condizione: gut. Akustik und Aerodynamik des Kraftfahrzeugs : Grundlagen - Optimierungsmethoden - Mess- und Versuchstechnik ; mit 11 Tabellen und 243 Literaturstellen ; [enthält die Beiträge der Tagung "Akustik und Aerodynamik des Kraftfahrzeuges", abgehalten im Haus der Technik e.V. am 1. und 2. Februar 1994] In deutscher Sprache. pages. …

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

Taschenbuch. Condizione: 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. Condizione: 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. Condizione: new. Paperback. Cet ouvrage presente une etude approfondie sur l'exploration de textes a l'aide de l'analyse du big data, selon une approche novatrice fondee sur la logique floue. Alors que le volume de donnees textuelles non structurees connait une croissance exponentielle sur les plateformes numeriques, l'extraction de connaissances pertinentes a partir d'ensembles de donnees a grande echelle est devenue un defi majeur. Cet ouvrage presente des methodologies avancees qui integrent les cadres de traitement du Big Data a la theorie des ensembles flous afin de gerer l'incertitude, l'ambiguite et le caractere vague inherents aux informations textuelles. Il explore les techniques de pretraitement, l'extraction de caracteristiques, l'analyse semantique et les strategies d'exploration evolutives concues pour les environnements de donnees a haute dimension. Un modele d'inference floue est propose pour ameliorer la precision de la classification, du regroupement en clusters et de la prise de decision dans des ensembles de donnees textuelles complexes. Des evaluations experimentales demontrent des performances ameliorees par rapport aux modeles traditionnels bases sur la logique criante. Cet ouvrage constitue une ressource precieuse pour les chercheurs, les universitaires et les professionnels travaillant dans les domaines de la science des donnees, de l'intelligence artificielle et de l'analyse du big data. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condizione: 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. …

Taschenbuch. Condizione: Neu. Minería de texto mediante big data | Rafeeq Ahmed (u. a.) | Taschenbuch | Spanisch | 2026 | Ediciones Nuestro Conocimiento | EAN 9786630178944 | 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. Condizione: new. Paperback. Cet ouvrage presente une etude approfondie sur l'exploration de textes a l'aide de l'analyse du big data, selon une approche novatrice fondee sur la logique floue. Alors que le volume de donnees textuelles non structurees connait une croissance exponentielle sur les plateformes numeriques, l'extraction de connaissances pertinentes a partir d'ensembles de donnees a grande echelle est devenue un defi majeur. Cet ouvrage presente des methodologies avancees qui integrent les cadres de traitement du Big Data a la theorie des ensembles flous afin de gerer l'incertitude, l'ambiguite et le caractere vague inherents aux informations textuelles. Il explore les techniques de pretraitement, l'extraction de caracteristiques, l'analyse semantique et les strategies d'exploration evolutives concues pour les environnements de donnees a haute dimension. Un modele d'inference floue est propose pour ameliorer la precision de la classification, du regroupement en clusters et de la prise de decision dans des ensembles de donnees textuelles complexes. Des evaluations experimentales demontrent des performances ameliorees par rapport aux modeles traditionnels bases sur la logique criante. Cet ouvrage constitue une ressource precieuse pour les chercheurs, les universitaires et les professionnels travaillant dans les domaines de la science des donnees, de l'intelligence artificielle et de l'analyse du big data. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…