Lingua: Inglese
Editore: Springer Verlag, Singapore, Singapore, 2025
ISBN 10: 9819778573 ISBN 13: 9789819778577
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Hardcover. Condizione: 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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Lingua: Inglese
Editore: Springer Verlag, Singapore, SG, 2025
ISBN 10: 9819778573 ISBN 13: 9789819778577
Da: Rarewaves USA, OSWEGO, IL, U.S.A.
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Lingua: Inglese
Editore: Springer Verlag, Singapore, SG, 2025
ISBN 10: 9819778573 ISBN 13: 9789819778577
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Aggiungi al carrelloTaschenbuch. Condizione: 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.
Lingua: Inglese
Editore: Springer Verlag, Singapore, SG, 2025
ISBN 10: 9819778573 ISBN 13: 9789819778577
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Aggiungi al carrelloTaschenbuch. Condizione: 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.
Lingua: Inglese
Editore: Springer, Palgrave Macmillan, 2025
ISBN 10: 9819778573 ISBN 13: 9789819778577
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Aggiungi al carrelloBuch. Condizione: 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.
Lingua: Inglese
Editore: Springer Verlag, Singapore, SG, 2025
ISBN 10: 9819778573 ISBN 13: 9789819778577
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Lingua: Inglese
Editore: Springer Verlag, Singapore, Singapore, 2025
ISBN 10: 9819778573 ISBN 13: 9789819778577
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Aggiungi al carrelloHardcover. Condizione: 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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Lingua: Inglese
Editore: Springer, Springer Jan 2026, 2026
ISBN 10: 9819778603 ISBN 13: 9789819778607
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 171,19
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Aggiungi al carrelloTaschenbuch. Condizione: 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.
Lingua: Inglese
Editore: Springer, Springer Jan 2025, 2025
ISBN 10: 9819778573 ISBN 13: 9789819778577
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 171,19
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Aggiungi al carrelloBuch. Condizione: 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.
Da: preigu, Osnabrück, Germania
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Aggiungi al carrelloBuch. Condizione: 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.
Lingua: Inglese
Editore: Springer, Springer Jan 2025, 2025
ISBN 10: 9819778573 ISBN 13: 9789819778577
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 171,19
Quantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: 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.
Lingua: Inglese
Editore: Springer, Springer Jan 2026, 2026
ISBN 10: 9819778603 ISBN 13: 9789819778607
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 171,19
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Aggiungi al carrelloTaschenbuch. Condizione: 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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