Abstract
Notifications received on the smartphone have become a vital part of typical work and social life. Notifications provide information ranging from important incoming business emails and meeting prompts to home deliveries and social interaction. But they can also become burdensome on the user as the average number of incoming notifications can be in the region of 100 per day. To cope with this overload a user might completely disable the notifications which will result in missing important information. This paper evaluates the user challenges, methods used to manage these challenges and discusses key challenges for data collection. In particular, we assess an overlap between user behaviour and situational context. This has led to the development of a hybrid model based on both behavioural and situational context to detect the best time to send the notification to the user.
Original language | English |
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Title of host publication | Proceedings of International Conference on Intelligent Emerging Methods of Artificial Intelligence & Cloud Computing |
Publisher | Springer Cham |
Pages | 11-21 |
Number of pages | 11 |
ISBN (Electronic) | 978-3-030-92905-3 |
ISBN (Print) | 978-3-030-92904-6 |
DOIs | |
Publication status | Published online - 5 May 2022 |
Event | International Conference on Integrated Emerging Methods of Artificial Intelligence & Cloud Computing - Virtual Mode, London, United Kingdom Duration: 26 Apr 2021 → 29 Apr 2021 Conference number: 2021 https://iemaicloud.org/ |
Publication series
Name | Smart Innovation, Systems and Technologies book series |
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Volume | 273 |
ISSN (Print) | 2190-3018 |
ISSN (Electronic) | 2190-3026 |
Conference
Conference | International Conference on Integrated Emerging Methods of Artificial Intelligence & Cloud Computing |
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Abbreviated title | IEMAICLOUD |
Country/Territory | United Kingdom |
City | London |
Period | 26/04/21 → 29/04/21 |
Internet address |
Keywords
- Ubiquitous computing
- Hybrid Model
- Notification Management System
- Machine Learning (ML)