US 2022/0067364 A1 · MACHINE LEARNING FOR DOCUMENT COMPRESSION

Abstract

In an example embodiment, machine learning is used to intelligently compress documents to reduce the overall footprint of storing large amounts of files for an organization. Specifically, a document is split into parts, with each part representing a grouping of text or an image. Optical character recognition is performed to identify the text in images. Machine learning techniques are then applied to a part of a document in order to determine how relevant the document is for the organization. The parts that are deemed to be not relevant may then be reduced in size, either by omitting them completely or by summarizing them. This allows for the compression to be tailored specifically to the organization, resulting in the ability to compress or eliminate parts of documents that other organizations might have found relevant (and thus would not have been compressed or eliminated through traditional means).

Claims20

Dependent claims

A system comprising:

at least one hardware processor;
and
a non-transitory computer-readable medium storing instructions that, when executed by the at least one hardware processor, cause the at least one hardware processor to perform operations comprising:
obtaining a document file from a document collection of an organization;
extracting one or more parts of the document file, the one or more parts including one or more image parts;
for each image part of the one or more image parts:
feeding the image part to a content decision engine, the content decision engine generating a relevancy score for the image part based on relevancy of the image part to the organization, the content decision engine utilizing a first machine learned model trained by a first machine learned algorithm using a set of training data unique to the organization;
based on the relevancy score for at least one image part of the one or more image parts, discarding the at least one image part;
and
compressing the document file by including only image parts that have not been discarded in a compressed version of the document file.

7 more elements

Dependencies are inferred from the claim text.

Machine learning for document compression

Life of this patent

Machine learning for document compression

Life of this patent

Abstract

Claims20