Everyday Apple approves around 900 NEW iOS and 50 new Mac Apps in the App Store[1]. In such a huge market, it is quite likely that some would try to game it.
The human curation approach falls flat on such a scale. Machine learning and natural language processing can help us in mining the App Store to detect anomalous behavior and improve the search and discovery of apps.
The statistical models of temporal distributions of ratings and rankings are still emerging and such hightlighting provide a useful resource to train the models. So if you see something, say something.
The human curation approach falls flat on such a scale. Machine learning and natural language processing can help us in mining the App Store to detect anomalous behavior and improve the search and discovery of apps.
The statistical models of temporal distributions of ratings and rankings are still emerging and such hightlighting provide a useful resource to train the models. So if you see something, say something.
[1] http://twitter.com/iapps_in