System and method to dynamically reconstruct portions of an electronic screen recording

A method, comprising:

• electronically dividing a first annotated frame into a first plurality of content portions, a second annotated frame into a second plurality of content portions, and a third annotated frame into a third plurality of content portions, wherein:
• the first annotated frame, the second annotated frame, and the third annotated frame being comprised in a plurality of annotated frames corresponding to an electronic recording of an electronic screen associated with a workspace device;
• the first annotated frame comprises a first timestamp, the first plurality of content portions, and first metadata;
• the second annotated frame comprises a second timestamp, the second plurality of content portions, and second metadata;
• and
• the third annotated frame comprises a third timestamp, the third plurality of content portions, and third metadata;
• electronically extracting a first plurality of labels from the first metadata, a second plurality of labels from the second metadata, and a third plurality of labels from the third metadata, wherein:
• each of the first plurality of labels correspond to one the first plurality of content portions;
• each of the second plurality of labels correspond to one of the second plurality of content portions;
• and
• each of the third plurality of labels correspond to one of the third plurality of content portions;
• training an artificial intelligence algorithm based at least in part upon input data representative of historical data associated with possible static layouts found in the electronic screen and expected dynamic content to be shown in the electronic screen;
• arranging, using the trained artificial intelligence algorithm, the first annotated frame, the second annotated frame, and the third annotated frame in in a recording order based on the first timestamp, the second timestamp, and the third timestamp;
• locating, using the trained artificial intelligence algorithm, a reference label in the first plurality of labels, the second plurality of labels, and the third plurality of labels matching a query type handled by the workspace device while the electronic recording of the electronic screen was performed;
• isolating, using the trained artificial intelligence algorithm, a first selected portion of the first plurality of content portions matching the reference label in the first annotated frame, a second selected portion of the second plurality of content portions matching the reference label in the second annotated frame, and a third selected portion of the third plurality of content portions matching the reference label in the third annotated frame;
• electronically separating, using the trained artificial intelligence algorithm, the first selected portion from the first plurality of content portions, the second selected portion from the second plurality of content portions, and the third selected portion from the third plurality of content portions;
• creating, using the trained artificial intelligence algorithm, a plurality of tracking parameters configured to track content changes in the first selected portion, the second selected portion, and the third selected portion based on the query type;
• tracking, in conjunction with the plurality of tracking parameters, a first content change between the first selected portion and the second selected portion and a second content change from the second selected portion to the third selected portion;
• deriving, using the trained artificial intelligence algorithm, a first intent associated with the first content change and a second intent associated with the second content change;
• determining, using the trained artificial intelligence algorithm, whether the first intent logically matches the query type;
• in response to determining that the first intent logically matches the query type, determining, using the trained artificial intelligence algorithm, whether the second intent logically matches the query type;
• and
• in response to determining that the second intent logically matches the query type, creating, using the trained artificial intelligence algorithm, an intelligent recording comprising the first selected portion, the second selected portion, and the third selected portion.

A non-transitory computer-readable medium storing instructions that when executed by a processor cause the processor to:

• electronically divide a first annotated frame into a first plurality of content portions, a second annotated frame into a second plurality of content portions, and a third annotated frame into a third plurality of content portions, wherein:
• the first annotated frame, the second annotated frame, and the third annotated frame being comprised in a plurality of annotated frames corresponding to an electronic recording of an electronic screen associated with a workspace device;
• the first annotated frame comprises a first timestamp, the first plurality of content portions, and first metadata;
• the second annotated frame comprises a second timestamp, the second plurality of content portions, and second metadata;
• and
• the third annotated frame comprises a third timestamp, the third plurality of content portions, and third metadata;
• electronically extract a first plurality of labels from the first metadata, a second plurality of labels from the second metadata, and a third plurality of labels from the third metadata, wherein:
• each of the first plurality of labels correspond to one the first plurality of content portions;
• each of the second plurality of labels correspond to one of the second plurality of content portions;
• and
• each of the third plurality of labels correspond to one of the third plurality of content portions;
• train an artificial intelligence algorithm based at least in part upon input data representative of historical data associated with possible static layouts found in the electronic screen and expected dynamic content to be shown in the electronic screen;
• arrange, using the trained artificial intelligence algorithm, the first annotated frame, the second annotated frame, and the third annotated frame in in a recording order based on the first timestamp, the second timestamp, and the third timestamp;
• locate, using the trained artificial intelligence algorithm, a reference label in the first plurality of labels, the second plurality of labels, and the third plurality of labels matching a query type handled by the workspace device while the electronic recording of the electronic screen was performed;
• isolate, using the trained artificial intelligence algorithm, a first selected portion of the first plurality of content portions matching the reference label in the first annotated frame, a second selected portion of the second plurality of content portions matching the reference label in the second annotated frame, and a third selected portion of the third plurality of content portions matching the reference label in the third annotated frame;
• electronically separate, using the trained artificial intelligence algorithm, the first selected portion from the first plurality of content portions, the second selected portion from the second plurality of content portions, and the third selected portion from the third plurality of content portions;
• create, using the trained artificial intelligence algorithm, a plurality of tracking parameters configured to track content changes in the first selected portion, the second selected portion, and the third selected portion based on the query type;
• track, in conjunction with the plurality of tracking parameters, a first content change between the first selected portion and the second selected portion and a second content change from the second selected portion to the third selected portion;
• derive, using the trained artificial intelligence algorithm, a first intent associated with the first content change and a second intent associated with the second content change;
• determine, using the trained artificial intelligence algorithm, whether the first intent logically matches the query type;
• in response to determining that the first intent logically matches the query type, determine, using the trained artificial intelligence algorithm, whether the second intent logically matches the query type;
• and
• in response to determining that the second intent logically matches the query type, create, using the trained artificial intelligence algorithm, an intelligent recording comprising the first selected portion, the second selected portion, and the third selected portion.