ATPP: A Mobile App Prediction System Based on Deep Marked Temporal Point Processes
Predicting the next application (app) a user will open is essential for improving the user
experience, eg, app pre-loading and app recommendation. Unlike previous solutions that …
experience, eg, app pre-loading and app recommendation. Unlike previous solutions that …
[PDF][PDF] ATPP: A Mobile App Prediction System Based on Deep Marked Temporal Point Processes
K YANG, XI ZHAO, J ZOU, WAN DU - 2023 - kangyangg.com
In a 2015 survey [33], almost 36% of mobile users demanded that app loading time should
be less than 2 seconds; 46% of iOS apps and 53% of Android apps take more than 2 …
be less than 2 seconds; 46% of iOS apps and 53% of Android apps take more than 2 …
[PDF][PDF] ATPP: A Mobile App Prediction System Based on Deep Marked Temporal Point Processes
K Yang, X Zhao, J Zou, W Du - sites.ucmerced.edu
Predicting the app that a user will open next is essential for improving user experience, eg,
app pre-loading. Unlike previous solutions that only predict next app's ID, this work also …
app pre-loading. Unlike previous solutions that only predict next app's ID, this work also …
ATPP: A Mobile App Prediction System Based on Deep Marked Temporal Point Processes
K Yang, X Zhao, J Zou, W Du - 2021 17th International …, 2021 - ieeexplore.ieee.org
Predicting the app that a user will open next is essential for improving user experience, eg,
app pre-loading. Unlike previous solutions that only predict next app's ID, this work also …
app pre-loading. Unlike previous solutions that only predict next app's ID, this work also …
[PDF][PDF] ATPP: A Mobile App Prediction System Based on Deep Marked Temporal Point Processes
K YANG, XI ZHAO, J ZOU, WAN DU - 2023 - kangyangg.com
In a 2015 survey [33], almost 36% of mobile users demanded that app loading time should
be less than 2 seconds; 46% of iOS apps and 53% of Android apps take more than 2 …
be less than 2 seconds; 46% of iOS apps and 53% of Android apps take more than 2 …
ATPP: A Mobile App Prediction System Based on Deep Marked Temporal Point Processes
K Yang, X Zhao, J Zou, W Du - 2021 17th International Conference on …, 2021 - computer.org
Predicting the app that a user will open next is essential for improving user experience, eg,
app pre-loading. Unlike previous solutions that only predict next app's ID, this work also …
app pre-loading. Unlike previous solutions that only predict next app's ID, this work also …
[PDF][PDF] ATPP: A Mobile App Prediction System Based on Deep Marked Temporal Point Processes
K YANG, XI ZHAO, J ZOU, WAN DU - 2023 - researchgate.net
In a 2015 survey [33], almost 36% of mobile users demanded that app loading time should
be less than 2 seconds; whereas 46% of iOS apps and 53% of Android apps consume more …
be less than 2 seconds; whereas 46% of iOS apps and 53% of Android apps consume more …
[PDF][PDF] ATPP: A Mobile App Prediction System Based on Deep Marked Temporal Point Processes
K Yang, X Zhao, J Zou, W Du - kangyangg.com
Predicting the app that a user will open next is essential for improving user experience, eg,
app pre-loading. Unlike previous solutions that only predict next app's ID, this work also …
app pre-loading. Unlike previous solutions that only predict next app's ID, this work also …
[PDF][PDF] ATPP: A Mobile App Prediction System Based on Deep Marked Temporal Point Processes
K Yang, X Zhao, J Zou, W Du - researchgate.net
Predicting the app that a user will open next is essential for improving user experience, eg,
app pre-loading. Unlike previous solutions that only predict next app's ID, this work also …
app pre-loading. Unlike previous solutions that only predict next app's ID, this work also …