Event attendance prediction in social networks / Xiaomei Zhang, Guohong Cao.
Zhang, Xiaomei, author.; Cao, Guohong, author.
2021
QA76.9.D343
Available Online

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Title Event attendance prediction in social networks / Xiaomei Zhang, Guohong Cao.
Author Zhang, Xiaomei, author.
ISBN 9783030892623 (electronic bk.)
303089262X (electronic bk.)
9783030892616 (print)
3030892611
DOI https://doi.org/10.1007/978-3-030-89262-3
Published Cham, Switzerland : Springer, 2021.
Language English
Description 1 online resource (viii, 54 pages) : illustrations (some color)
Item Number 10.1007/978-3-030-89262-3 doi
Call Number QA76.9.D343
Dewey Decimal Classification 006.3/12
Summary 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.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Digital File Characteristics text file PDF
Source of Description Online resource; title from PDF title page (SpringerLink, viewed January 7, 2022).
Added Author Cao, Guohong, author.
Series SpringerBriefs in statistics, 2191-5458
Available in Other Form Print version: 9783030892616
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
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Introduction
Related Work
Data Collection
Event Attendance Prediction
Performance Evaluations
Conclusions and Future Research Directions.

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