THESIS
2018
Abstract
The news media these days use mobile applications to reach out to their users. Users
are ubiquitously equipped with mobile devices, and pushing notifications to them can
improve the user experience. In this thesis, mobile notification opening data of 1.8
million users amounting to 240 million log-records in a real mobile news application,
Apple Daily, is collected for 2 months and studied. A framework is designed for effective
mobile notification delivery to the end users to improve their average notification opening
rate and response time. It is the first work to propose a model to quantify notification
effectiveness in terms of the number of notifications received in a given time. A method
of grouping similar locations based on their social nature or function is then described...[
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The news media these days use mobile applications to reach out to their users. Users
are ubiquitously equipped with mobile devices, and pushing notifications to them can
improve the user experience. In this thesis, mobile notification opening data of 1.8
million users amounting to 240 million log-records in a real mobile news application,
Apple Daily, is collected for 2 months and studied. A framework is designed for effective
mobile notification delivery to the end users to improve their average notification opening
rate and response time. It is the first work to propose a model to quantify notification
effectiveness in terms of the number of notifications received in a given time. A method
of grouping similar locations based on their social nature or function is then described,
and compared to existing feature-based location grouping methods. Correlations among
the location groups are identified based on user preferences for news categories, and
clusters of location groups are observed based on news categories read. These are then
used in a novel convex optimization scheme to increase users overall notification opening
rate and reduce their notification response times. This work is also the first to address
the problem of notification recommendation as an optimization problem. The method
shows an improvement of the average user notification opening rate by up to 62.4%,
and that of the average user response time by up to 17.2%, depending on the location
grouping algorithm used.
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