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

Claim 10:
11. An apparatus for intelligent editing of legal documents, the apparatus comprising:
at least a processor; and
a memory communicatively connected to the at least a processor, the memory containing instructions configuring the at least a processor to:
receive a rule, wherein the rule is a language parameter;
access a plurality of documents;
generate a list of tokens as a function of the rule and the plurality of documents;
score, 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;
rank each token of the list of tokens as a function of a frequency of occurrence in the plurality of documents and a ranking model is 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;
access a user-inputted legal text;
classify the user-inputted legal text to a document type using a document type classifier;
identify a target text of the user-inputted legal text as a function of the document type;
generate one or more suggested alterations to the target text of the user-inputted legal text as a function of the ranked list of tokens;
display the one or more suggested alterations to the target text of the user-inputted legal text to a user;
monitor at least one suggested alteration implementation to the 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 further comprises:
receiving user data comprising a user response to the at least one suggested alteration implementation; and

iteratively train 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.