Smarter Push Notifications in Multi-Device Environments
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The number of internet-connected devices a person interacts with has increased. With this increase comes an increase in the number of devices available to notify the user of new information. This paper proposes an algorithm for intelligently selecting the primary device that should first interrupt the user with new information. This algorithm fuses information such as activity level and movement from all of a user's devices to predict which device is best. This algorithm is then implemented as a push-notification service. Using this service, and implemented clients for Android and Google Chrome, we test this algorithm to establish both its ability to predict the user's preferred device and that it reduces the annoyance level of users. Our results confirm that our algorithm has the ability to select an appropriate device, in the future more accurately predict the correct device, and finally that it is less annoying than a naive approach.
Abstract
The number of internet-connected devices a person interacts with has increased. With this increase comes an increase in the number of devices available to notify the user of new information. This paper proposes an algorithm for intelligently selecting the primary device that should first interrupt the user with new information. This algorithm fuses information such as activity level and movement from all of a user's devices to predict which device is best. This algorithm is then implemented as a push-notification service. Using this service, and implemented clients for Android and Google Chrome, we test this algorithm to establish both its ability to predict the user's preferred device and that it reduces the annoyance level of users. Our results confirm that our algorithm has the ability to select an appropriate device, in the future more accurately predict the correct device, and finally that it is less annoying than a naive approach.
참고문헌 (19)
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