US 2021/0240937 A1Published application

System and method for artificial intelligence driven document analysis, including automated reuse of predictive coding rules based on management and curation of datasets or models

AssigneeCs Disco, Inc.

InventorsAlan Justin Lockett, Verlyn Michael Fischer, Richard Alan Vestal, Jesse Abraham Ramos, Robert Duane Harrington, Brian Daniel Luskey

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Abstract

Artificial intelligence based document analysis systems and methods are disclosed. Embodiments of document analysis systems may allow the reuse of coded datasets defined in association with a particular code by allowing these datasets to be bundled to define a dataset for another code, where that code may be associated with a target corpus of documents. A model can then be trained based on that dataset and used to provide predictive scores for the documents of the target corpora with respect to the code. Furthermore, this code can be applied not just to the target corpus of documents, but additionally can be applied against any other corpora.

Claims21

Dependent claims

A system for document analysis comprising:

a processor;
a data store, comprising a first target corpus of electronic document and a second target corpus of electronic documents;
and
a non-transitory computer readable medium comprising instructions for:
receiving a definition of a first code in association with the first target corpus;
creating a first dataset for the first code;
receiving an indication that the first code is to be boosted with a second code, wherein the second code is associated with the second target corpus and the second code is associated with a second dataset, the second dataset comprising a first set of positive signals associated with the second code and documents of the second corpus and a first set of negative signals associated with the second code and documents of the second target corpus;
adding the second dataset associated with the second code and the second target corpus to the first dataset of the first code such that the first dataset comprises a boosting dataset including the second dataset comprising the first set of positive signals associated with the second code and documents of the second corpus and the first set of negative signals associated with the second code and documents of the second target corpus;
training a first machine learning model for the first code on the boosting dataset of the first dataset;
generating predictive scores for the first code for documents of the first target corpus using the first machine learning model;
and
presenting the predictive scores in association with documents of the first target corpus to a user.

9 more elements

A method for document analysis comprising:

receiving a definition of a first code in association with a first target corpus of electronic documents;
creating a first dataset for the first code;
receiving an indication that the first code is to be boosted with a second code, wherein the second code is associated with a second target corpus of electronic documents and the second code is associated with a second dataset, the second dataset comprising a first set of positive signals associated with the second code and documents of the second corpus and a first set of negative signals associated with the second code and documents of the second target corpus;
adding the second dataset associated with the second code and the second target corpus to the first dataset of the first code such that the first dataset comprises a boosting dataset including the second dataset comprising the first set of positive signals associated with the second code and documents of the second corpus and the first set of negative signals associated with the second code and documents of the second target corpus;
training a first machine learning model for the first code on the boosting dataset of the first dataset;
generating predictive scores for the first code for documents of the first target corpus using the first machine learning model;
and
presenting the predictive scores in association with documents of the first target corpus to a user.

5 more elements

A non-transitory computer readable medium, comprising instruction for:

receiving a definition of a first code in association with a first target corpus of electronic documents;
creating a first dataset for the first code;
receiving an indication that the first code is to be boosted with a second code, wherein the second code is associated with a second target corpus of electronic documents and the second code is associated with a second dataset, the second dataset comprising a first set of positive signals associated with the second code and documents of the second corpus and a first set of negative signals associated with the second code and documents of the second target corpus;
adding the second dataset associated with the second code and the second target corpus to the first dataset of the first code such that the first dataset comprises a boosting dataset including the second dataset comprising the first set of positive signals associated with the second code and documents of the second corpus and the first set of negative signals associated with the second code and documents of the second target corpus;
training a first machine learning model for the first code on the boosting dataset of the first dataset;
generating predictive scores for the first code for documents of the first target corpus using the first machine learning model;
and
presenting the predictive scores in association with documents of the first target corpus to a user.

5 more elements

Dependencies are inferred from the claim text.

Facts

Application: 16/881,274Filed 22 May 2020
Priority: 31 Jan 2020
Published: 5 Aug 2021
Term ends: Not estimatedThe source records don’t support an estimate.

Classification9 codes

G06N 20/20
Machine learning: ensemble learning
G06F 40/30
Handling natural language data: semantic analysis
G06N 3/08
Neural networks: learning methods
G06N 3/09
Learning methods: supervised learning

Family

Application62/968,659Us provisional application · filed 31 Jan 2020
US 11,416,685 B2Related patent
US 2021/0240937 A1This patent

From the US filing history. Foreign family members aren’t listed.

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