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Vorhersage und Analyse des Navigationsverhaltens von Webnutzern

Vorhersage und Analyse des Navigationsverhaltens von Webnutzern


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About the Book

Das Hauptaugenmerk liegt auf dem Problem der Erstellung von Modellen, die das frühere Nutzerverhalten darstellen und die in der Lage sind, die wahrscheinlichsten Links vorherzusagen, die ein Nutzer beim Betrachten einer Seite anfordert. WUM wurde speziell für die Durchführung von Anwendungen durch Analyse der Nutzungsdaten entwickelt. Die Ergebnisse des Grey-Clustering-Algorithmus werden als Input für das Grey Moving Probability Markov Model verwendet, um den nächsten Besuch der Nutzer vorherzusagen. Dieser Ansatz modelliert Navigationssitzungen und die Vorhersage des nächsten Navigationsschritts unter Verwendung von Übergangswahrscheinlichkeiten mit zwei Schätzungsansätzen. Die Vorhersage ist ein Weg, historische Informationen zu analysieren, um die höchstmögliche Wahrscheinlichkeit der nächsten Anfrage zu berechnen; das Browsing-Muster, wenn die zukünftigen Benutzer und Kunden auf der Website surfen, wird abgeglichen. Es gibt viele webbasierte Vorteile, um die Vorhersage zu implementieren, wie z. B. Website-Personalisierung, strukturierte Website, Business Intelligence usw. Die Transaktionswahrscheinlichkeiten eignen sich besser für die Vorhersage der nächsten Anfrage der Nutzer. Im Vorhersagemodell wird eine Markov-Kette variabler Länge verwendet, um die Kategorie des nächsten Zustands des Benutzers mit der Transaktionswahrscheinlichkeit vorherzusagen.


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Product Details
  • ISBN-13: 9786206905455
  • Publisher: KS Omniscriptum Publishing
  • Binding: Paperback
  • Language: German
  • Returnable: N
  • Weight: 462 gr
  • ISBN-10: 6206905454
  • Publisher Date: 01 Dec 2023
  • Height: 229 mm
  • No of Pages: 280
  • Spine Width: 16 mm
  • Width: 152 mm


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Vorhersage und Analyse des Navigationsverhaltens von Webnutzern
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Vorhersage und Analyse des Navigationsverhaltens von Webnutzern
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