Systems and methods for seamless application of autocorrection and provision of review insights through adapted user interface

A system comprising:

• at least one processor;
• and
• a memory, operatively connected with the at least one processor, storing computer-executable instructions that, when executed by the at least one processor, causes the at least one processor to execute a method that comprises:
• detecting one or more content portions for autocorrection in an electronic document that is presented through a user interface of an application or service;
• generating a classification identification classifying a type of correction to be executed for the one or more content portions;
• selecting a timing as when to apply an autocorrection for the correction by applying a trained machine learning model adapted to select when to apply the autocorrection based on a collective analysis of:
• the classification identification,
• a determined location of the one or more content portions within one or more sentences of the electronic document, and
• confidence scoring adapted to determine whether to apply the autocorrection during a receipt of typing input based on analysis of the classification identification and the determined location;
• automatically applying, at the timing selected in the selecting, the autocorrection to the one or more content portions in the electronic document;
• and
• presenting a user interface menu comprising a graphical user interface feature identifying a list of autocorrections automatically applied to the electronic document, wherein each autocorrection in the list of autocorrections is presented and prioritized in the user interface menu based on the confidence scoring, and wherein the autocorrections that have a confidence score that exceeded a threshold value by less than a specific value are positioned higher in the list of autocorrections than autocorrections that have a confidence score that exceeded the threshold value by more than the specific value.

A method comprising:

• detecting, on a server device, one or more content portions for autocorrection in an electronic document;
• generating a classification identification classifying a type of correction to be executed for the one or more content portions;
• selecting a timing as when to apply an autocorrection for the correction by applying a trained machine learning model adapted to select when to apply the autocorrection based on a collective analysis of:
• the classification identification,
• a determined location of the one or more content portions within one or more sentences of the electronic document, and
• confidence scoring adapted to determine whether to apply the autocorrection during a receipt of typing input based on analysis of the classification identification and the determined location;
• automatically generating, at the timing selected in the selecting, the autocorrection to the one or more content portions in the electronic document;
• and
• causing a user interface menu comprising a graphical user interface feature identifying a list of autocorrections automatically applied to the electronic document to be presented, wherein each autocorrection in the list of autocorrections is caused to be presented and prioritized in the user interface menu based on the confidence scoring, and wherein the autocorrections that have a confidence score that exceeded a threshold value by less than a specific value are positioned higher in the list of autocorrections than autocorrections that have a confidence score that exceeded the threshold value by more than the specific value.