Machine Learning to Optimize Smartphone Notifications

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Taiwan-based researchers developed a method to optimize smartphone notifications by utilizing machine learning technique called as C-3PO

Push notifications send by apps can occupy space leading to slow performance of smartphone. A new AI method developed by Ton Ton Hsieng-De Huang and Hung-Yu Kao on arXiv.org, might help to optimize notifications. The data was provided by Leopard Mobile, a Taiwan-based internet company. This machine learning technology is called as C-3PO (heh). It works by analyzing browsing history, shopping history, and financial details of user.

According to the article, the neural network analyses the pop-up notifications received by user and which ones they clicked on. As a result, AI was able to make push notifications smarter reducing the number of overall notifications and increasing the click through rates on the ones that did appear. The team is working on improving the neural network model by decreasing the number of complex tasks.

Furthermore, developers intend to apply this model to a system that advertisers could use to optimize when and how often they are delivering ads. The easiest solution to decreasing push notifications is to turn off notifications or delete an app altogether. This new technology will provide users and app developer’s better option to manage data traffic in their smartphone.

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