Information processing system, document type identification method, and model generation method

An information processing system comprising:

• circuitry configured to:
• acquire a character recognition result of each of a plurality of training images including a plurality of predetermined document type images that are images of documents of a predetermined document type having layouts different from one another;
• acquire a frequently occurring word string of the predetermined document type;
• detect the frequently occurring word string from the character recognition result of each of the plurality of training images to acquire information on a position of the frequently occurring word string in a document depicted in the training image;
• generate a feature quantity of the document depicted in the training image using the information on the position of the frequently occurring word string in the document depicted in each of the plurality of training images, the feature quantity including a positional relationship feature quantity related to a positional relationship between the frequently occurring word string and another word string in the document depicted in the training image;
• and
• generate a trained model that identifies the predetermined document type, the trained model being generated through machine learning using training data,
• the training data associating the feature quantity of the document depicted in each of the plurality of training images with information indicating whether the document depicted in the training image is a document of the predetermined document type.

A document type identification method comprising:

• acquiring a character recognition result of an identification target image that is an image of an identification target document;
• storing a frequently occurring word string of a predetermined document type;
• detecting the frequently occurring word string from the character recognition result of the identification target image to acquire information on a position of the frequently occurring word string in the identification target document;
• generating a feature quantity of the identification target document using the information on the position, the feature quantity including a positional relationship feature quantity related to a positional relationship between the frequently occurring word string and another word string in the identification target document;
• storing a trained model that identifies the predetermined document type, the trained model being generated through machine learning such that, in response to input of a feature quantity of a document including a positional relationship feature quantity related to a positional relationship between the frequently occurring word string and another word string in the document, information indicating appropriateness of the document being a document of the predetermined document type is output;
• and
• inputting the feature quantity of the identification target document to the trained model to identify whether the identification target document is a document of the predetermined document type.

A model generation method comprising:

• acquiring a character recognition result of each of a plurality of training images including a plurality of predetermined document type images that are images of documents of a predetermined document type having layouts different from one another;
• acquiring a frequently occurring word string of the predetermined document type;
• detecting the frequently occurring word string from the character recognition result of each of the plurality of training images to acquire information on a position of the frequently occurring word string in a document depicted in the training image;
• generating a feature quantity of the document depicted in the training image, using the information on the position of the frequently occurring word string in the document depicted in each of the plurality of training images, the feature quantity including a positional relationship feature quantity related to a positional relationship between the frequently occurring word string and another word string in the document depicted in the training image;
• and
• generating a trained model that identifies the predetermined document type, the trained model being generated through machine learning using training data,
• the training data associating the feature quantity of the document depicted in each of the plurality of training images with information indicating whether the document depicted in the training image is a document of the predetermined document type.