AppJoy: Personalized Mobile Application Discovery

by Bo Yan and Guanling Chen

This paper introduces the author's app AppJoy, which collects users' usage of apps on a mobile device, derives the similarity scores between apps based on the usage and recommend apps based on similarity scores. The idea is to utilize the time and spatial information along with the apps. Contrastive to other recommendation algorithm, based on ratings, the app usage may serve as a much better feature. I guess this shows a simpler model with strong feature might serve better than a complicated model with weak features.

It seems that, if we decide to move on to applications in mobile devices, we'd better get to know the details of the mobile platforms. E.g. IOS might not allow you to collect such usage information. So the experiments can only be done on Android.