Automatic Selection of Images for an Application
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.
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.