Text Clustering with Enhanced Novel Fast Seeds Affinity Propagation - Couverture souple

Krithika, M Meena

9786209106750: Text Clustering with Enhanced Novel Fast Seeds Affinity Propagation

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ISBN 10 : 6209106757 ISBN 13 : 9786209106750

Editeur : LAP Lambert Academic Publishing, 2025

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�diteur: LAP Lambert Academic Publishing
Date d'�dition: 2025
Langue: anglais
ISBN 10: 6209106757
ISBN 13: 9786209106750
Reliure: Broch�
Nombre de pages: 56
Coordonn�es du fabricant: non disponible
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Text Clustering with Enhanced Novel Fast Seeds Affinity Propagation

Krithika, M Meena

Edit� par LAP LAMBERT Academic Publishing, 2025

ISBN 10 : 6209106757 ISBN 13 : 9786209106750

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Text Clustering with Enhanced Novel Fast Seeds Affinity Propagation

Krithika, M Meena

Edit� par LAP Lambert Academic Publishing, 2025

ISBN 10 : 6209106757 ISBN 13 : 9786209106750

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Text Clustering with Enhanced Novel Fast Seeds Affinity Propagation

Krithika, M Meena

Edit� par LAP LAMBERT Academic Publishing, 2025

ISBN 10 : 6209106757 ISBN 13 : 9786209106750

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Text Clustering with Enhanced Novel Fast Seeds Affinity Propagation (Paperback)

M. Meena Krithika

Edit� par LAP Lambert Academic Publishing, 2025

ISBN 10 : 6209106757 ISBN 13 : 9786209106750

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Paperback. Etat : new. Paperback. Text clustering is an essential technique in text mining and natural language processing for organizing large volumes of unstructured data into meaningful groups. Traditional clustering algorithms often face challenges in scalability, efficiency, and accuracy when dealing with high-dimensional text data. This work proposes an enhanced approach using Novel Fast Seeds Affinity Propagation (NFAP) to improve clustering performance. By introducing optimized seed selection, the method accelerates convergence, reduces computational complexity, and enhances the quality of cluster formation. Experimental results demonstrate that the proposed model achieves superior clustering accuracy and efficiency compared to standard affinity propagation methods, making it suitable for large-scale text mining applications. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N� de r�f. du vendeur 9786209106750

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Text Clustering with Enhanced Novel Fast Seeds Affinity Propagation

M. Meena Krithika

Edit� par LAP LAMBERT Academic Publishing Nov 2025, 2025

ISBN 10 : 6209106757 ISBN 13 : 9786209106750

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 56 pp. Englisch. N� de r�f. du vendeur 9786209106750

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Text Clustering with Enhanced Novel Fast Seeds Affinity Propagation

Krithika, M Meena

Edit� par LAP Lambert Academic Publishing, 2025

ISBN 10 : 6209106757 ISBN 13 : 9786209106750

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Text Clustering with Enhanced Novel Fast Seeds Affinity Propagation (Paperback)

M. Meena Krithika

Edit� par LAP Lambert Academic Publishing, 2025

ISBN 10 : 6209106757 ISBN 13 : 9786209106750

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Paperback. Etat : new. Paperback. Text clustering is an essential technique in text mining and natural language processing for organizing large volumes of unstructured data into meaningful groups. Traditional clustering algorithms often face challenges in scalability, efficiency, and accuracy when dealing with high-dimensional text data. This work proposes an enhanced approach using Novel Fast Seeds Affinity Propagation (NFAP) to improve clustering performance. By introducing optimized seed selection, the method accelerates convergence, reduces computational complexity, and enhances the quality of cluster formation. Experimental results demonstrate that the proposed model achieves superior clustering accuracy and efficiency compared to standard affinity propagation methods, making it suitable for large-scale text mining applications. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N� de r�f. du vendeur 9786209106750

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Text Clustering with Enhanced Novel Fast Seeds Affinity Propagation

Krithika, M Meena

Edit� par LAP Lambert Academic Publishing, 2025

ISBN 10 : 6209106757 ISBN 13 : 9786209106750

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Text Clustering with Enhanced Novel Fast Seeds Affinity Propagation (Paperback)

M. Meena Krithika

Edit� par LAP Lambert Academic Publishing, 2025

ISBN 10 : 6209106757 ISBN 13 : 9786209106750

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Paperback. Etat : new. Paperback. Text clustering is an essential technique in text mining and natural language processing for organizing large volumes of unstructured data into meaningful groups. Traditional clustering algorithms often face challenges in scalability, efficiency, and accuracy when dealing with high-dimensional text data. This work proposes an enhanced approach using Novel Fast Seeds Affinity Propagation (NFAP) to improve clustering performance. By introducing optimized seed selection, the method accelerates convergence, reduces computational complexity, and enhances the quality of cluster formation. Experimental results demonstrate that the proposed model achieves superior clustering accuracy and efficiency compared to standard affinity propagation methods, making it suitable for large-scale text mining applications. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N� de r�f. du vendeur 9786209106750

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Text Clustering with Enhanced Novel Fast Seeds Affinity Propagation

M. Meena Krithika

Edit� par LAP LAMBERT Academic Publishing Nov 2025, 2025

ISBN 10 : 6209106757 ISBN 13 : 9786209106750

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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Text clustering is an essential technique in text mining and natural language processing for organizing large volumes of unstructured data into meaningful groups. Traditional clustering algorithms often face challenges in scalability, efficiency, and accuracy when dealing with high-dimensional text data. This work proposes an enhanced approach using Novel Fast Seeds Affinity Propagation (NFAP) to improve clustering performance. By introducing optimized seed selection, the method accelerates convergence, reduces computational complexity, and enhances the quality of cluster formation. Experimental results demonstrate that the proposed model achieves superior clustering accuracy and efficiency compared to standard affinity propagation methods, making it suitable for large-scale text mining applications.VDM Verlag, Dudweiler Landstra�e 99, 66123 Saarbr�cken 56 pp. Englisch. N� de r�f. du vendeur 9786209106750

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