Techniques of Prefetching Operation Cost Based Digital Content and Digital Content With Emphasis

Abstract

Techniques for prefetching operation cost based digital content and digital content with emphasis that overcome the challenges of conventional systems are described. In one example, a computing device may receive digital content representations of digital content from a service provider system, which are displayed on a user interface of the computing device. Thereafter, the computing device may also receive digital content as prefetches having a changed display characteristic as emphasizing a portion of the digital content based on a model trained using machine learning. Alternatively, the computing device may receive digital content as a prefetch based on a model trained using machine learning in which the model addresses a likelihood of conversion of a good or service and an operation cost of providing the digital content. Upon receiving a user input selecting one of the digital content representations, digital content is rendered in the user interface of the computing device.

What is claimed is: 
     
         1 . A method implemented by a computing device, the method comprising:
 transmitting, by the computing device, a representation corresponding to digital content to be displayed in a user interface associated with a client device;   determining, by the computing device, whether to change a display characteristic of the digital content by determining a probability of interaction with the digital content with the changed display characteristic based on a model trained using machine learning; and   responsive to determining that the display characteristic of the digital content is to be changed, transmitting, by the computing device, the digital content with the changed display characteristic to the client device as a prefetch, the representation selectable to cause display of the digital content with the changed display characteristic in the user interface associated with the client device.   
     
     
         2 . The method as described in  claim 1 , wherein the changed display characteristic includes an amount of emphasis on a portion of the digital content, the emphasis including at least one of bolding or highlighting. 
     
     
         3 . The method as described in  claim 1 , wherein the changed display characteristic includes at least one of a badge or a label. 
     
     
         4 . The method as described in  claim 1 , wherein the model trained using machine learning is trained using training data that describes user interactions. 
     
     
         5 . The method as described in  claim 4 , wherein the user interactions include at least one of clicking data, scrolling data, and eye movement data. 
     
     
         6 . The method as described in  claim 4 , further comprising:
 receiving real-time data related to real-time user interactions with the digital content;   training the model using machine learning with the real-time data and the training data; and   wherein the determining is based on the trained model.   
     
     
         7 . The method as described in  claim 4 , further comprising:
 determining a relationship between the changed display characteristic and a likelihood of interaction with the digital content based on the model trained using machine learning with the training data; and   determining a location of the changed display characteristic based on the relationship.   
     
     
         8 . The method as described in  claim 1 , wherein the changed display characteristic is a changed position on the user interface associated with the client device. 
     
     
         9 . The method as described in  claim 1 , wherein the digital content with the changed display characteristic as the prefetch is transmitted to the client device before user selection of the representation in the user interface associated with the client device. 
     
     
         10 . A computing device comprising:
 a processor; and   computer-readable storage media having instructions stored thereon that, responsive to execution by the processor, causes the processor to perform operations comprising:
 transmitting a representation corresponding to digital content to be displayed in a user interface associated with a client device; 
 determining whether to change a display characteristic of the digital content by determining a probability of interaction with the digital content with the changed display characteristic based on a model trained using machine learning; and 
 responsive to determining that the display characteristic of the digital content is to be changed, transmitting the digital content with the changed display characteristic to the client device as a prefetch, the representation selectable to cause display of the digital content with the changed display characteristic in the user interface associated with the client device. 
   
     
     
         11 . The computing device as described in  claim 10 , wherein the changed display characteristic includes an amount of emphasis on the digital content, the emphasis including at least one of adding a border or changing a background color. 
     
     
         12 . The computing device as described in  claim 10 , wherein the changed display characteristic includes at least one of a badge or a label. 
     
     
         13 . The computing device as described in  claim 10 , wherein the changed display characteristic does not change a location on the user interface where the prefetched digital content with the changed display characteristic is to be rendered. 
     
     
         14 . The computing device as described in  claim 10 , wherein the digital content as the prefetch is transmitted before the user selection of the representation in the user interface associated with the client device. 
     
     
         15 . One or more computer-readable storage media comprising instructions stored thereon that, responsive to execution by a processing system, causes the processing system to perform operations comprising:
 transmitting a representation corresponding to digital content to be displayed in a user interface associated with a client device;   determining whether to change a display characteristic of the digital content by determining a probability of interaction with the digital content with the changed display characteristic based on a model trained using machine learning; and   responsive to determining that the display characteristic of the digital content is to be changed, transmitting the digital content with the changed display characteristic to the client device as a prefetch, the representation selectable to cause display of the digital content with the changed display characteristic in the user interface associated with the client device.   
     
     
         16 . One or more computer-readable storage media as described in  claim 15 , wherein the changed display characteristic is a changed position on the user interface associated with the client device. 
     
     
         17 . One or more computer-readable storage media as described in  claim 15 , wherein the digital content as the prefetch is transmitted before the user selection of the representation in the user interface associated with the client device. 
     
     
         18 . One or more computer-readable storage media as described in  claim 15 , wherein the model trained using machine learning is trained using training data that describes user interactions. 
     
     
         19 . One or more computer-readable storage media as described in  claim 18 , the operations further comprising:
 determining a relationship between the changed display characteristic and a likelihood of interaction with the digital content based on the model trained using machine learning with the training data; and   determining a location of the changed display characteristic based on the relationship.   
     
     
         20 . One or more computer-readable storage media as described in  claim 18 , wherein the user interactions include at least one of clicking data, scrolling data, and eye movement data.