Abstract: A method and system for performing optical character recognition (OCR) error correction is disclosed. The method includes receiving at least one document image. One or more text entities are determined in the data using an OCR technique. A character embedding, a layout embedding, and a style embedding is determined of each of the one or more text entities in the at least one document image. A concatenated embedding is determined of each of the one or more text entities based on the corresponding character embedding, style embedding, and layout embedding of each of the one or more text entities. A corrected character embedding of each character recognized in the corresponding text entity based on the corresponding concatenated embedding using an encoder-decoder model.

Abstract: A method and system of grouping a plurality of documents is disclosed. The method includes determining a plurality of text features of each of the plurality of documents. A plurality of image features of each of the plurality of documents are determined. A layout features set of each of the plurality of documents are determined based on the plurality of text features and the plurality of image features. Each of the plurality of documents in one group from a set of groups is grouped based on determination of a document layout of each of the plurality of documents.

Abstract: A method and system for performing optical character recognition (OCR) error correction is disclosed. The method includes receiving at least one document image. One or more text entities are determined in the data using an OCR technique. A character embedding, a layout embedding, and a style embedding is determined of each of the one or more text entities in the at least one document image. A concatenated embedding is determined of each of the one or more text entities based on the corresponding character embedding, style embedding, and layout embedding of each of the one or more text entities. A corrected character embedding of each character recognized in the corresponding text entity based on the corresponding concatenated embedding using an encoder-decoder model.

Abstract: A method and system of grouping a plurality of documents is disclosed. The method includes determining a plurality of text features of each of the plurality of documents. A plurality of image features of each of the plurality of documents are determined. A layout features set of each of the plurality of documents are determined based on the plurality of text features and the plurality of image features. Each of the plurality of documents in one group from a set of groups is grouped based on determination of a document layout of each of the plurality of documents.