SYSTEM AND METHOD FOR RECOMMENDING FEATURES FOR CONTENT PRESENTATIONS
A method, a system, and an article are provided for developing and using a predictive model for analyzing and creating items of content. An example method includes: providing a plurality of items of content in which each item of content includes an image, a video, and/or a sound; extracting a plurality of features from each item of content; determining a performance indicator for each item of content, wherein the performance indicator provides an indication of user responses to presentations of the item of content; developing a model to predict the performance indicator for each item of content based on the plurality of features; based on the model, determining a sensitivity between the performance indicator and each feature; and developing a new item of content based on the determined sensitivities.
1 . A method, comprising:
providing a plurality of items of content, each item of content comprising at least one of an image, a video, a sound, and any combination thereof;
extracting a plurality of features from each item of content;
determining a performance indicator for each item of content, the performance indicator comprising an indication of user responses to presentations of the item of content;
developing a model to predict the performance indicator for each item of content based on the plurality of features;
based on the model, determining a sensitivity between the performance indicator and each feature; and
developing a new item of content based on the determined sensitivities.
2 . The method of claim 1 , wherein providing the plurality of items of content comprises:
presenting the plurality of items of content on user client devices.
3 . The method of claim 1 , wherein extracting the plurality of features comprises:
using at least one of computer vision, convolutional neural networks, and combinations thereof.
4 . The method of claim 1 , wherein the plurality of features comprises at least one element in a digital image.
5 . The method of claim 1 , wherein determining the performance indicator for each item of content comprises:
determining user responses to presentations of the item of content on user client devices.
6 . The method of claim 5 , wherein the user responses comprise user interactions with the item of content on the user client devices.
7 . The method of claim 1 , wherein the model comprises a regression model.
8 . The method of claim 1 , wherein developing the new item of content comprises:
identifying a subset of the plurality of features comprising highest sensitivities.
9 . The method of claim 1 , wherein developing the new item of content comprises modifying an existing item of content.
10 . The method of claim 1 , further comprising:
presenting the new item of content on a plurality of user client devices;
determining the performance indicator for the new item of content; and
updating the model based on the performance indicator for the new item of content.
11 . A system, comprising:
one or more computer processors programmed to perform operations comprising:
providing a plurality of items of content, each item of content comprising at least one of an image, a video, a sound, and any combination thereof;
extracting a plurality of features from each item of content;
determining a performance indicator for each item of content, the performance indicator comprising an indication of user responses to presentations of the item of content;
developing a model to predict the performance indicator for each item of content based on the plurality of features;
based on the model, determining a sensitivity between the performance indicator and each feature; and
developing a new item of content based on the determined sensitivities.
12 . The system of claim 11 , wherein providing the plurality of items of content comprises:
presenting the plurality of items of content on user client devices.
13 . The system of claim 11 , wherein the plurality of features comprises at least one element in a digital image.
14 . The system of claim 11 , wherein determining the performance indicator for each item of content comprises:
determining user responses to presentations of the item of content on user client devices.
15 . The system of claim 14 , wherein the user responses comprise user interactions with the item of content on the user client devices.
16 . The system of claim 11 , wherein the model comprises a regression model.
17 . The system of claim 11 , wherein developing the new item of content comprises:
identifying a subset of the plurality of features comprising highest sensitivities.
18 . The system of claim 11 , wherein developing the new item of content comprises modifying an existing item of content.
19 . The system of claim 11 , further comprising:
presenting the new item of content on a plurality of user client devices;
determining the performance indicator for the new item of content; and
updating the model based on the performance indicator for the new item of content.
20 . An article, comprising:
a non-transitory computer-readable medium having instructions stored thereon that, when executed by one or more computer processors, cause the computer processors to perform operations comprising:
providing a plurality of items of content, each item of content comprising at least one of an image, a video, a sound, and any combination thereof;
extracting a plurality of features from each item of content;
determining a performance indicator for each item of content, the performance indicator comprising an indication of user responses to presentations of the item of content;
developing a model to predict the performance indicator for each item of content based on the plurality of features;
based on the model, determining a sensitivity between the performance indicator and each feature; and
developing a new item of content based on the determined sensitivities.