Machine learning based document editing engine

A system, comprising:

• at least one data processor;
• and
• at least one memory storing instructions which, when executed by the at least one data processor, result in operations comprising:
• training a machine learning model by at least processing, with the machine learning model, training data including a first matrix corresponding to a first attribute and a second matrix corresponding to a second attribute, the first matrix including one or more values indicating whether one or more contract clauses are present in a document having the first attribute, the second matrix including one or more values indicating whether the one or more contract clauses are present in a document having the second attribute, and the machine learning model being trained, based at least on the first matrix and the second matrix, to identify one or more correlations between the first attribute, the second attribute, and a presence of the one or more contract clauses;
• receiving, from a client, one or more inputs associated with a first document;
• generating, by at least processing the one or more inputs with the trained machine learning model, a recommendation to include a first contract clause from the first document, the trained machine learning model generating the recommendation based at least on the first contract clause being included in a second document having one or more attributes and/or content in common with the first document;
• and
• providing, to the client, the recommendation to exclude the first contract clause from the first document.

A computer-implemented method, comprising:

• training a machine learning model by at least processing, with the machine learning model, training data including a first matrix corresponding to a first attribute and a second matrix corresponding to a second attribute, the first matrix including one or more values indicating whether one or more contract clauses are present in a document having the first attribute, the second matrix including one or more values indicating whether the one or more contract clauses are present in a document having the second attribute, and the machine learning model being trained, based at least on the first matrix and the second matrix, to identify one or more correlations between the first attribute, the second attribute, and a presence of the one or more contract clauses;
• receiving, from a client, one or more inputs associated with a first document;
• generating, by at least processing the one or more inputs with the trained machine learning model, a recommendation to include a first contract clause from the first document, the trained machine learning model generating the recommendation based at least on the first contract clause being included in a second document having one or more attributes and/or content in common with the first document;
• and
• providing, to the client, the recommendation to exclude the first contract clause from the first document.

A non-transitory computer readable medium storing instructions, which when executed by at least one data processor, result in operations comprising:

• training a machine learning model by at least processing, with the machine learning model, training data including a first matrix corresponding to a first attribute and a second matrix corresponding to a second attribute, the first matrix including one or more values indicating whether one or more contract clauses are present in a document having the first attribute, the second matrix including one or more values indicating whether the one or more contract clauses are present in a document having the second attribute, and the machine learning model being trained, based at least on the first matrix and the second matrix, to identify one or more correlations between the first attribute, the second attribute, and a presence of the one or more contract clauses;
• receiving, from a client, one or more inputs associated with a first document;
• generating, by at least processing the one or more inputs with the trained machine learning model, a recommendation to include a first contract clause from the first document, the trained machine learning model generating the recommendation based at least on the first contract clause being included in a second document having one or more attributes and/or content in common with the first document;
• and
• providing, to the client, the recommendation to exclude the first contract clause from the first document.