Téléchargez le livre : Event Attendance Prediction in Social Networks

Event Attendance Prediction in Social Networks

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Springer


Collection :

SpringerBriefs in Statistics

Paru le : 2022-01-01

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Description

This volume focuses on predicting users’ attendance at a future event at specific time and location based on their common interests. Event attendance prediction has attracted considerable attention because of its wide range of potential applications. By predicting event attendance, events that better fit users’ interests can be recommended, and personalized location-based or topic-based services related to the events can be provided to users. Moreover, it can help event organizers estimating the event scale, identifying conflicts, and help manage resources. This book first surveys existing techniques on event attendance prediction and other related topics in event-based social networks. It then introduces a context-aware data mining approach to predict the event attendance by learning how users are likely to attend future events. Specifically, three sets of context-aware attributes are identified by analyzing users’ past activities, including semantic, temporal, and spatial attributes. This book illustrates how these attributes can be applied for event attendance prediction by incorporating them into supervised learning models, and demonstrates their effectiveness through a real-world dataset collected from event-based social networks. 
Pages
54 pages
Collection
SpringerBriefs in Statistics
Parution
2022-01-01
Marque
Springer
EAN papier
9783030892616
EAN PDF
9783030892623
Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
5
Taille du fichier
2447 Ko
Prix
63,29 €
EAN EPUB
9783030892623
Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
5
Taille du fichier
3768 Ko
Prix
63,29 €

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