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Automatic selection of images for an application

An image and new application technology, applied in the direction of reasoning methods, electrical components, transmission systems, etc., can solve problems that affect user installation

Inactive Publication Date: 2017-08-29
GOOGLE LLC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Often, the content a developer provides to promote an app can influence whether a user chooses to install and / or purchase an app

Method used

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  • Automatic selection of images for an application
  • Automatic selection of images for an application
  • Automatic selection of images for an application

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0011] Embodiments disclosed herein automatically select images and / or screenshots that are likely to be more successful in marketing the game than instances where a developer selects an image and / or video. Recommended images and / or videos may also reach specific audiences more effectively. Additionally, developers can spend less time deciding which images best display or advertise an app's features. For example, in some instances, the system may recommend images that may increase the likelihood that an end user of an application store will download an application.

[0012] Typically, when an app developer attempts to publish a game or upload a game to an app store, the developer submits one or more screenshots. In some instances, developers may upload thousands of images. However, the app store may allow the developer to show a limited number of screenshots (eg, ten images) and / or videos (including limitations on the length and / or size of the videos). In some configuration...

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Abstract

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.

Description

Background technique [0001] App stores provide app developers with a way to distribute their apps to a user base. An application store may provide indications of user ratings, downloads, user reviews, images, videos, descriptions, related applications, and the like. In some cases, the application store may generate recommendations for one or more applications based on the user's purchase history, the user's browsing history, the user's friends' purchases, downloads, ratings of the applications, and the like. As a way to market the app to end users, the developer may upload some of the content offered through the app store, such as images and / or videos. For example, a screenshot may be visible to an end user when the user views an application's page on an application store. Often, the content a developer provides to promote an app may influence whether a user chooses to install and / or purchase the app. However, end users may not spend much time thinking about the app, such a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/02
CPCG06Q30/02G06N5/048H04L67/10
Inventor 赫里希凯什·阿拉德海耶阿图尔·库马尔
Owner GOOGLE LLC