In this article we will disclose the work that we have been doing to discover stories tuned based on the statistics that we collect and feedback received.Īt Storyo we have been always concerned with speed and designed our algorithms to provide a seamless experience for our users. In the Storyo app and now in Storyo SDK we have been always focused on giving the best experience for final users by designing a story discovery strategy that best matches how people tend to remember moments and having in mind how the mobile operating systems work.
Deep learning execution to be viable has to run on GPU or dedicated HW and it should be noted that iOS does not allow access to the GPU while the app is in background to avoid a possible impact on an app running in foreground and to avoid unexpected battery drain. When searching for stories on a mobile device one should also look at the degrees of freedom to execute them. For example, if a relevant story is found, a user can be send a push notification and, thus, promote return rate and increase conversion. On the other end, home events or moments happening quite frequently like going to an office of one’s company in a different city or even in a different country tend to be all messed up and are remembered as less relevant moments.Īn additional aspect of automatic stories that is worth emphasizing is that they can be used to communicate naturally with users even when the app is not explicitly running. Stories are strongly related to space and time where the event occurred and temporal scale of our memory tends to increase in special occurrences like travel scenarios. You can then create stories for photos classified as beach, sunset, flowers, with an endless set of categories or simply select the “best ones” according to some criteria and constraint it to a specific date span.Īnother possible approach to search for stories is by trying to get closer to how our brain tends to organize memories. The discovery of these stories can follow different strategies and probably the most common way to do it today is through deep learning to classify photos based on their content or recaps like “best of 2018”.
Automatic discover of stories based on a device camera roll or a cloud backup system became an important strategy to increase return rate of apps dealing with photos and photo memories in particular.
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