Patent ID: 11954135
Assignee: nan
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method for intelligent editing of legal documents, the method comprising:
receiving, by a processor, a rule, wherein the rule is a language parameter;
accessing, by the processor, a plurality of documents;
generating, by the processor, a list of tokens as a function of the rule and the plurality of documents;
scoring, the plurality of documents, as a function of the list of tokens, wherein scoring further comprises using a machine learning model wherein the machine learning model utilizes training data correlating documents and tokens;
ranking, by the processor, each token of the list of tokens as a function of a frequency of occurrence in the plurality of documents and a ranking model trained using ranking training data comprising historical data relating a plurality of source documents to a score and the plurality of documents and the score for the plurality of documents;
accessing, by the processor, a user-inputted legal text;
classifying, by the processor, the user-inputted legal text to a document type using a document type classifier;
identifying, by the processor, a target text of the user-inputted legal text as a function of the document type;
generating, by the processor, one or more suggested alterations to the target text of the user-inputted legal text as a function of the scoring of the plurality of documents;
displaying the one or more suggested alterations to the target text of the user-inputted legal text to a user;
monitoring, by the processor, at least one suggested alteration implementation to target text of the user-inputted legal text, wherein:
the at least one suggested alteration implementation comprises at least a modification to the target text of the user-inputted legal text; and
monitoring the at least one suggested alteration implementation to the target text of the user-inputted legal text further comprises:
receiving user data comprising a user response to the at least one suggested alteration implementation; and

iteratively training, by the processor, the ranking model as a function of the user data, wherein iteratively training the ranking model comprises:
generating a first post-modification score of a first version of the user-inputted legal text generated as a function of the user data; and
iteratively training the ranking model based on the first post-modification score until a second version of the user-inputted legal text associated with a second post-modification score is generated, wherein the second post-modification score is higher than the first post-modification score.