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ISBN 10: 9819778573 ISBN 13: 9789819778577
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Añadir al carritoHardcover. Condición: new. Hardcover. This edited book consolidates and documents recent research on topic modeling in text mining using Latent Dirichlet Allocation (LDA). Written by leading experts in topic modeling, it covers a wide range of areas, such as theory building, systematic research, and innovative applications. This book offers a thorough exploration of the latest advancements in topic modeling. From identifying issues in unstructured text data to categorizing documents and extracting valuable insights, the book provides practical use of LDA as a powerful tool in qualitative and quantitative research. The chapters discuss the rapidly evolving landscape of topic modeling algorithms and offer tangible examples and applications of LDA in educational research, showcasing its real-world impact. This book dives into the heart of educational research and uncovers the transformative potential of Latent Dirichlet Allocation in shaping the future of topic modeling. This book is a valuable resource, highlighting exemplary works and rapid advances in the field. It appeals to students, researchers, and practitioners interested in text mining. This edited book consolidates and documents recent research on topic modeling in text mining using Latent Dirichlet Allocation (LDA). This book dives into the heart of educational research and uncovers the transformative potential of Latent Dirichlet Allocation in shaping the future of topic modeling. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Idioma: Inglés
Publicado por Springer Verlag, Singapore, SG, 2025
ISBN 10: 9819778573 ISBN 13: 9789819778577
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Añadir al carritoTaschenbuch. Condición: Neu. Text Mining in Educational Research | Topic Modeling and Latent Dirichlet Allocation | Myint Swe Khine | Taschenbuch | ix | Englisch | 2026 | Springer | EAN 9789819778607 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Idioma: Inglés
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This edited book consolidates and documents recent research on topic modeling in text mining using Latent Dirichlet Allocation (LDA). Written by leading experts in topic modeling, it covers a wide range of areas, such as theory building, systematic research, and innovative applications. This book offers a thorough exploration of the latest advancements in topic modeling. From identifying issues in unstructured text data to categorizing documents and extracting valuable insights, the book provides practical use of LDA as a powerful tool in qualitative and quantitative research. The chapters discuss the rapidly evolving landscape of topic modeling algorithms and offer tangible examples and applications of LDA in educational research, showcasing its real-world impact. This book dives into the heart of educational research and uncovers the transformative potential of Latent Dirichlet Allocation in shaping the future of topic modeling. This book is a valuable resource, highlighting exemplary works and rapid advances in the field. It appeals to students, researchers, and practitioners interested in text mining.
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Publicado por Springer, Palgrave Macmillan, 2025
ISBN 10: 9819778573 ISBN 13: 9789819778577
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This edited book consolidates and documents recent research on topic modeling in text mining using Latent Dirichlet Allocation (LDA). Written by leading experts in topic modeling, it covers a wide range of areas, such as theory building, systematic research, and innovative applications. This book offers a thorough exploration of the latest advancements in topic modeling. From identifying issues in unstructured text data to categorizing documents and extracting valuable insights, the book provides practical use of LDA as a powerful tool in qualitative and quantitative research. The chapters discuss the rapidly evolving landscape of topic modeling algorithms and offer tangible examples and applications of LDA in educational research, showcasing its real-world impact. This book dives into the heart of educational research and uncovers the transformative potential of Latent Dirichlet Allocation in shaping the future of topic modeling. This book is a valuable resource, highlighting exemplary works and rapid advances in the field. It appeals to students, researchers, and practitioners interested in text mining.
Idioma: Inglés
Publicado por Springer Verlag, Singapore, SG, 2025
ISBN 10: 9819778573 ISBN 13: 9789819778577
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Añadir al carritoHardcover. Condición: new. Hardcover. This edited book consolidates and documents recent research on topic modeling in text mining using Latent Dirichlet Allocation (LDA). Written by leading experts in topic modeling, it covers a wide range of areas, such as theory building, systematic research, and innovative applications. This book offers a thorough exploration of the latest advancements in topic modeling. From identifying issues in unstructured text data to categorizing documents and extracting valuable insights, the book provides practical use of LDA as a powerful tool in qualitative and quantitative research. The chapters discuss the rapidly evolving landscape of topic modeling algorithms and offer tangible examples and applications of LDA in educational research, showcasing its real-world impact. This book dives into the heart of educational research and uncovers the transformative potential of Latent Dirichlet Allocation in shaping the future of topic modeling. This book is a valuable resource, highlighting exemplary works and rapid advances in the field. It appeals to students, researchers, and practitioners interested in text mining. This edited book consolidates and documents recent research on topic modeling in text mining using Latent Dirichlet Allocation (LDA). This book dives into the heart of educational research and uncovers the transformative potential of Latent Dirichlet Allocation in shaping the future of topic modeling. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Idioma: Inglés
Publicado por Springer, Springer Jan 2025, 2025
ISBN 10: 9819778573 ISBN 13: 9789819778577
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This edited book consolidates and documents recent research on topic modeling in text mining using Latent Dirichlet Allocation (LDA). Written by leading experts in topic modeling, it covers a wide range of areas, such as theory building, systematic research, and innovative applications. This book offers a thorough exploration of the latest advancements in topic modeling. From identifying issues in unstructured text data to categorizing documents and extracting valuable insights, the book provides practical use of LDA as a powerful tool in qualitative and quantitative research. The chapters discuss the rapidly evolving landscape of topic modeling algorithms and offer tangible examples and applications of LDA in educational research, showcasing its real-world impact. This book dives into the heart of educational research and uncovers the transformative potential of Latent Dirichlet Allocation in shaping the future of topic modeling. This book is a valuable resource, highlighting exemplary works and rapid advances in the field. It appeals to students, researchers, and practitioners interested in text mining. 168 pp. Englisch.
Idioma: Inglés
Publicado por Springer, Springer Jan 2026, 2026
ISBN 10: 9819778603 ISBN 13: 9789819778607
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 171,19
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This edited book consolidates and documents recent research on topic modeling in text mining using Latent Dirichlet Allocation (LDA). Written by leading experts in topic modeling, it covers a wide range of areas, such as theory building, systematic research, and innovative applications. This book offers a thorough exploration of the latest advancements in topic modeling. From identifying issues in unstructured text data to categorizing documents and extracting valuable insights, the book provides practical use of LDA as a powerful tool in qualitative and quantitative research. The chapters discuss the rapidly evolving landscape of topic modeling algorithms and offer tangible examples and applications of LDA in educational research, showcasing its real-world impact. This book dives into the heart of educational research and uncovers the transformative potential of Latent Dirichlet Allocation in shaping the future of topic modeling. This book is a valuable resource, highlighting exemplary works and rapid advances in the field. It appeals to students, researchers, and practitioners interested in text mining. 168 pp. Englisch.
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Añadir al carritoBuch. Condición: Neu. Text Mining in Educational Research | Topic Modeling and Latent Dirichlet Allocation | Myint Swe Khine | Buch | ix | Englisch | 2025 | Springer | EAN 9789819778577 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
Idioma: Inglés
Publicado por Springer, Springer Jan 2025, 2025
ISBN 10: 9819778573 ISBN 13: 9789819778577
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 171,19
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This edited book consolidates and documents recent research on topic modeling in text mining using Latent Dirichlet Allocation (LDA). Written by leading experts in topic modeling, it covers a wide range of areas, such as theory building, systematic research, and innovative applications. This book offers a thorough exploration of the latest advancements in topic modeling. From identifying issues in unstructured text data to categorizing documents and extracting valuable insights, the book provides practical use of LDA as a powerful tool in qualitative and quantitative research. The chapters discuss the rapidly evolving landscape of topic modeling algorithms and offer tangible examples and applications of LDA in educational research, showcasing its real-world impact. This book dives into the heart of educational research and uncovers the transformative potential of Latent Dirichlet Allocation in shaping the future of topic modeling. This book is a valuable resource, highlighting exemplary works and rapid advances in the field. It appeals to students, researchers, and practitioners interested in text mining.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 168 pp. Englisch.
Idioma: Inglés
Publicado por Springer, Springer Jan 2026, 2026
ISBN 10: 9819778603 ISBN 13: 9789819778607
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 171,19
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This edited book consolidates and documents recent research on topic modeling in text mining using Latent Dirichlet Allocation (LDA). Written by leading experts in topic modeling, it covers a wide range of areas, such as theory building, systematic research, and innovative applications. This book offers a thorough exploration of the latest advancements in topic modeling. From identifying issues in unstructured text data to categorizing documents and extracting valuable insights, the book provides practical use of LDA as a powerful tool in qualitative and quantitative research. The chapters discuss the rapidly evolving landscape of topic modeling algorithms and offer tangible examples and applications of LDA in educational research, showcasing its real-world impact. This book dives into the heart of educational research and uncovers the transformative potential of Latent Dirichlet Allocation in shaping the future of topic modeling. This book is a valuable resource, highlighting exemplary works and rapid advances in the field. It appeals to students, researchers, and practitioners interested in text mining.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 168 pp. Englisch.
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