IP Library › Granted Patent US 12711307
Granted Patent B2
US 12711307 · App. 18/655,433 · Granted Aug 18, 2026

Delivery of electronic communications utilizing validated electronic communication templates

Inventors: Luis Fabio Cruz Aguirre (Canoas, BR); Renata De Paris (Porto Alegre, BR); Ronaldo Radaieski Cunda (Porto Alegre, BR)
Assignee: Dell Products L.P.
G06F40/186G06F40/106
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Quick Facts
Patent No.
US 12711307
App. No.
18/655,433
Granted
Aug 18, 2026
Kind
B2
Abstract

An apparatus comprises at least one processing device configured to obtain an electronic communication template, to generate a first data structure characterizing features of a base electronic communication generated utilizing the electronic communication template, and to generate a second data structure characterizing features of preview electronic communications rendered utilizing the electronic communication template for different information technology asset configurations. The at least one processing device is also configured to utilize one or more machine learning models to generate a third data structure characterizing similarity between the features of the base and preview electronic communications based on the first and second data structures, to validate the electronic communication template for use with at least one information technology asset configuration based on the third data structure, and to deliver electronic communications to information technology assets having the at least one information technology asset configuration utilizing the validated electronic communication template.

Claims (46)

1 . An apparatus comprising:

at least one processing device comprising a processor coupled to a memory;

the at least one processing device being configured:

to obtain an electronic communication template;

to generate a first data structure characterizing one or more features of a base electronic communication generated utilizing the electronic communication template;

to generate one or more second data structures characterizing one or more features of one or more preview electronic communications rendered utilizing the electronic communication template for one or more information technology asset configurations;

to utilize one or more machine learning models, which take as input the first and the one or more second data structures, to generate a third data structure characterizing similarity between the one or more features of the base electronic communication generated utilizing the electronic communication template and the one or more features of the one or more preview electronic communications rendered utilizing the electronic communication template for the one or more information technology asset configurations;

to validate the electronic communication template for use with at least one of the one or more information technology asset configurations based at least in part on the third data structure; and

to deliver electronic communications to one or more information technology assets having said at least one of the one or more information technology asset configurations utilizing the validated electronic communication template.

2 . The apparatus of claim 1 wherein the electronic communication template comprises an email template.

3 . The apparatus of claim 1 wherein the one or more features of the base electronic communication generated utilizing the electronic communication template and the one or more features of the one or more preview electronic communications rendered utilizing the electronic communication template for the one or more information technology asset configurations comprise one or more visual features.

4 . The apparatus of claim 3 wherein the one or more visual features comprise at least one of positions and sizes of visual elements.

5 . The apparatus of claim 1 wherein the one or more features of the base electronic communication generated utilizing the electronic communication template and the one or more features of the one or more preview electronic communications rendered utilizing the electronic communication template for the one or more information technology asset configurations comprise one or more textual features.

6 . The apparatus of claim 5 wherein the one or more textual features comprise at least one of text font, text size, and locations of text displayed.

7 . The apparatus of claim 5 wherein the one or more textual features of the base electronic communication generated utilizing the electronic communication template and the one or more textual features of the one or more preview electronic communications rendered utilizing the electronic communication template for the one or more information technology asset configurations are determined by:

identifying one or more regions of interest containing text;

generating bounding boxes for each word recognized in the identified one or more regions of interest containing text; and

merging the bounding boxes for each word to generate one or more additional bounding boxes for sentences in the identified one or more regions of interest containing text.

8 . The apparatus of claim 1 wherein the one or more features of the base electronic communication generated utilizing the electronic communication template and the one or more features of the one or more preview electronic communications rendered utilizing the electronic communication template for the one or more information technology asset configurations comprise (i) one or more visual features and (ii) one or more textual features.

9 . The apparatus of claim 8 wherein the one or more machine learning models comprises:

a first machine learning model configured for determining similarity between the one or more visual features of the base electronic communication generated utilizing the electronic communication template and the one or more visual features of the one or more preview electronic communications rendered utilizing the electronic communication template for the one or more information technology asset configurations; and

a second machine learning model configured for determining similarity between the one or more textual features of the base electronic communication generated utilizing the electronic communication template and the one or more textual features of the one or more preview electronic communications rendered utilizing the electronic communication template for the one or more information technology asset configurations.

10 . The apparatus of claim 1 wherein the one or more machine learning models comprises a Siamese Neural Network (SNN) model.

11 . The apparatus of claim 10 wherein the SNN model utilizes a triplet loss function with a pre-trained Convolutional Neural Network (CNN) subnetwork and transfer learning from a subset of neural network layers of the pre-trained CNN subnetwork.

12 . The apparatus of claim 1 wherein the one or more information technology asset configurations comprise hardware configurations of devices utilized in rendering the one or more preview electronic communications.

13 . The apparatus of claim 1 wherein the one or more information technology asset configurations comprise software configurations of one or more software applications utilized in rendering the one or more preview electronic communications.

14 . The apparatus of claim 1 wherein said at least one of the one or more information technology asset configurations correspond to at least one of the one or more preview electronic communications having at least a threshold similarity with the base electronic communication generated utilizing the electronic communication template.

15 . A computer program product comprising a non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code when executed by at least one processing device causes the at least one processing device:

to obtain an electronic communication template;

to generate a first data structure characterizing one or more features of a base electronic communication generated utilizing the electronic communication template;

to generate one or more second data structures characterizing one or more features of one or more preview electronic communications rendered utilizing the electronic communication template for one or more information technology asset configurations;

to utilize one or more machine learning models, which take as input the first and the one or more second data structures, to generate a third data structure characterizing similarity between the one or more features of the base electronic communication generated utilizing the electronic communication template and the one or more features of the one or more preview electronic communications rendered utilizing the electronic communication template for the one or more information technology asset configurations;

to validate the electronic communication template for use with at least one of the one or more information technology asset configurations based at least in part on the third data structure; and

to deliver electronic communications to one or more information technology assets having said at least one of the one or more information technology asset configurations utilizing the validated electronic communication template.

16 . The computer program product of claim 15 wherein the electronic communication template comprises an email template.

17 . The computer program product of claim 15 wherein the one or more features of the base electronic communication generated utilizing the electronic communication template and the one or more features of the one or more preview electronic communications rendered utilizing the electronic communication template for the one or more information technology asset configurations comprise (i) one or more visual features and (ii) one or more textual features.

18 . A method comprising:

obtaining an electronic communication template;

generating a first data structure characterizing one or more features of a base electronic communication generated utilizing the electronic communication template;

generating one or more second data structures characterizing one or more features of one or more preview electronic communications rendered utilizing the electronic communication template for one or more information technology asset configurations;

utilizing one or more machine learning models, which take as input the first and the one or more second data structures, to generate a third data structure characterizing similarity between the one or more features of the base electronic communication generated utilizing the electronic communication template and the one or more features of the one or more preview electronic communications rendered utilizing the electronic communication template for the one or more information technology asset configurations;

validating the electronic communication template for use with at least one of the one or more information technology asset configurations based at least in part on the third data structure; and

delivering electronic communications to one or more information technology assets having said at least one of the one or more information technology asset configurations utilizing the validated electronic communication template;

wherein the method is performed by at least one processing device comprising a processor coupled to a memory.

19 . The method of claim 18 wherein the electronic communication template comprises an email template.

20 . The method of claim 18 wherein the one or more features of the base electronic communication generated utilizing the electronic communication template and the one or more features of the one or more preview electronic communications rendered utilizing the electronic communication template for the one or more information technology asset configurations comprise (i) one or more visual features and (ii) one or more textual features.