Information processing apparatus, information processing system, information processing method, and storage medium

Patent metadata

Field	Value
Publication number	US-2024193370-A1
Application number	US-202318533685-A
Country	US
Kind code	A1
Filing date	Dec 8, 2023
Priority date	Dec 13, 2022
Publication date	Jun 13, 2024
Grant date	—

Abstract

To make it possible to extract a character string corresponding to each extraction-target item with accuracy even in a case where the character string ranges of a plurality of extraction-target items overlap one another in the task of named entity recognition. By using a training model trained to extract a character string corresponding to each of a plurality of items within a document, a character string corresponding to each of the plurality of items is extracted and output for an input document image. Then, a character string corresponding to an item among the plurality of items, for which a corresponding character string is not extracted, is re-extracted from the character string output by the first extracting.

First claim

What is claimed is:

1 . An information processing apparatus comprising:
one or more memories storing instructions; and one or more processors executing the instructions to perform:
first extracting to extract, by using a training model trained to extract a character string corresponding to each of a plurality of items within a document, a character string corresponding to each of the plurality of items for an input document image; and
second extracting to extract a character string corresponding to an item among the plurality of items, for which a corresponding character string is not extracted by the first extracting, from the character string obtained by the first extracting.

2 . The information processing apparatus according to claim 1 , wherein
the second extracting is performed by using the training model used for the first extracting, whose input and output are limited.

3 . The information processing apparatus according to claim 1 , wherein
the second extracting is performed by using a training model different from the training model used for the first extracting, which is trained to extract a character string corresponding to a second item different from a first item from a character string corresponding to the first item of the plurality of items.

4 . The information processing apparatus according to claim 1 , wherein
in the second extracting, key-value extracting is performed, to which a keyword and a data type corresponding to an item among the plurality of items, for which a corresponding character string is not extracted by the first extracting, are set.

5 . The information processing apparatus according to claim 1 , wherein
the one or more processors further execute the instructions to perform setting an extraction-target item in the second extracting in advance and the second extracting is performed in a case where the item among the plurality of items, for which a corresponding character string is not extracted by the first extracting, is the extraction-target item set in advance.

6 . The information processing apparatus according to claim 1 , wherein
the one or more processors further execute the instructions to perform causing a display unit to display a UI screen on which results of the first extracting are shown, on the UI screen, a UI element for a user to give instructions to perform the second extracting exists, and based on user instructions via the UI screen, the second extracting is performed.

7 . The information processing apparatus according to claim 6 , wherein
the UI element is displayed on the UI screen in association with the item among the plurality of items, for which a corresponding character string is not extracted by the first extracting and in the second extracting, a character string corresponding to the item with which the UI element is associated is extracted.

8 . An information processing system comprising:
a training device generating a training model by performing training for extracting a character string corresponding to each of a plurality of items from a document image; and an information processing apparatus performing first extracting to extract, by using the training model, a character string corresponding to each of the plurality of items for an input document image and second extracting to extract a character string corresponding to an item among the plurality of items, for which a corresponding character string is not extracted by the first extracting, from the character string obtained by the first extracting.

9 . The information processing system according to claim 8 , wherein
the second extracting is performed by using the training model used for the first extracting, whose input and output are limited.

10 . The information processing system according to claim 8 , wherein
the second extracting is performed by using a training model different from the training model used for the first extracting and the training device further generates the other different training model by performing training for extracting a character string corresponding to a second item different from a first item from a character string corresponding to the first item of the plurality of items.

11 . The information processing system according to claim 8 , wherein
in the second extracting, key-value extracting is performed, to which a keyword and a data type corresponding to an item among the plurality of items, for which a corresponding character string is not extracted by the first extracting, are set.

12 . An information processing method comprising the steps of:
performing first extracting to extract, by using a training model trained to extract a character string corresponding to each of a plurality of items within a document, a character string corresponding to each of the plurality of items for an input document image; and performing second extracting to extract a character string corresponding to an item among the plurality of items, for which a corresponding character string is not extracted by the first extracting, from the character string obtained by the first extracting.

13 . A non-transitory computer readable storage medium storing a program for causing a computer to perform an information processing method comprising the steps of:
performing first extracting to extract, by using a training model trained to extract a character string corresponding to each of a plurality of items within a document, a character string corresponding to each of the plurality of items for an input document image; and performing second extracting to extract a character string corresponding to an item among the plurality of items, for which a corresponding character string is not extracted by the first extracting, from the character string obtained by the first extracting.

Assignees

• Canon Kk

Inventors

• Achiwa Ken

Classifications

• G06V30/10

  Character recognition · CPC title

• G06F40/295 Primary

  Named entity recognition · CPC title