Images and/or videos may be recommended to a developer based on a classifier. The classifier may determine an application metric that may measure the likelihood that an application is successful for applications on an application store. The system may extract and/or determine features from images and/or videos associated with a training set of applications that are deemed successful. A classifier may be trained on the training set of applications to determine which features of the images and/or videos are associated with the application metric. The classifier may be applied to new and/or existing applications on the application store to generate a recommendation of which images the developer of the application should use to increase the likelihood that the application will be successful.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A computer-implemented method, comprising: determining, by a server of an application store, an application metric for each of a plurality of applications hosted by the application store, wherein the application metric is a composite score based on at least one of: a conversion statistic, a download statistic, a rating, a retention statistic, and a popularity statistic; selecting a first of the plurality of applications based on the application metric; obtaining a plurality of features for a plurality of images associated with the first of the plurality of applications on the application store; and obtaining a classifier by determining a feature set comprising a portion of the plurality of features that correspond to the plurality of features that are correlated with the application metric. 2. The method of claim 1, further comprising selecting the first of the plurality of applications based on an application category. 3. The method of claim 1, wherein the plurality of images is obtained from a plurality of videos associated with the first of the plurality of applications. 4. The method of claim 1, further comprising: receiving, by the server, a plurality of images for a new application from a client device; applying the classifier to the plurality of images for the new application; selecting a subset of the plurality of images for the new application; and presenting the subset of the plurality of images to the client device. 5. The method of claim 4, further comprising: determining a category for the new application; and applying a classifier corresponding to the category to the new application. 6. The method of claim 4, further comprising receiving permission from the client device to provide the subset of the plurality of images for the new application to a plurality of users of the application store through application store. 7. The method of claim 4, further comprising ranking the subset of the plurality of images for the new application. 8. The method of claim 4, further comprising receiving a selection of the presented images by the client device. 9. The method of claim 1, wherein obtaining the classifier comprises training the classifier on the first of the plurality of applications, wherein the first of the plurality of applications have a value of the application metric above a threshold. 10. A system, comprising: a database associated with an application store, the database configured to store an application metric, wherein the application metric is a composite score based on at least one of: a conversion statistic, a download statistic, a rating, a retention statistic, and a popularity statistic; a processor associated with the application store and that is communicatively coupled to the database, the processor configured to: determine an application metric for each of a plurality of applications hosted by the application store; select a first of the plurality of applications based on the application metric; obtain a plurality of features for a plurality of images associated with the first of the plurality of applications on the application store; and obtain a classifier by determining a feature set comprising a portion of the plurality of features that correspond to the plurality of features that are correlated with the application metric. 11. The system of claim 10, further configured to select the first of the plurality of applications based on an application category. 12. The system of claim 10, wherein the plurality of images is obtained from a plurality of videos associated with the first of the plurality of applications. 13. The system of claim 10, the processor further configured to: receive a plurality of images for a new application from a client device; apply the classifier to the plurality of images for the new application; select a subset of the plurality of images for the new application; and present the subset of the plurality of images to the client device. 14. The system of claim 13, the processor further configured to: determine a category for the new application; and apply a classifier corresponding to the category to the new application. 15. The system of claim 13, the processor further configured to receive permission from the client device to provide the subset of the plurality of images for the new application to a plurality of users of the application store through application store. 16. The system of claim 13, the processor further configured to rank the subset of the plurality of images for the new application. 17. The system of claim 13, the processor further configured to receive a selection of the presented images by the client device. 18. The system of claim 10, wherein obtaining the classifier comprises training the classifier on the first of the plurality of applications, wherein the first of the plurality of applications have a value of the application metric above a threshold.