Accenture Global Solutions Limited

Tsunghan Wu

Guanglei Xiong

Emmanuel Munguia Tapia

Colin Connors

Anwitha Paruchuri

Neeru Narang

Chung-Sheng Li

Madhura Shivaram

Sukryool Kang

Benjamin Nathan Grosof

Kayhan Moharreri

Ditty Mathew

Kyle Patrick Johnson

Mingzhu Lu

Anshuma Chandak

Golnaz Ghasemiesfeh

A document processing system processes documents including typewritten and/or handwritten data by converting them to document images for entity extraction. A received document is initially processed to generate a deep document data structured and for classification as one of a structured or an unstructured document. If the document is classified as a structured document, it is processed for entity extraction based on a matching template and image alignment of the document image with the matching template. If the document is classified as an unstructured document, entities are extracted by obtaining nodes and providing the nodes to a self-supervised masked visual language model.

Deep document processing with self-supervised learning

A data extraction and expansion system receives documents with data to be processed, extracts a set of a specific type of entities from the received documents, expands the set of entities by retrieving additional entities of the specific type from an ontology and other external data sources to improve the match between the received documents. The ontology includes data regarding entities and relationships between entities. The ontology is built by extracting the entity and relationship information from external data sources and can be constantly updated. If the additional entities to expand the set of entities cannot be retrieved from the ontology then a real-time search of the external data sources is executed to retrieve the additional entities from the external data sources.

Section segmentation based information retrieval with entity expansion

A system for determining a response to a query includes a receiver to receive a query along with a plurality of potential responses to the query. A detector detects a topic and a type of the query based on information extracted from text and structure. Further, a selector selects at least one of a plurality of techniques for processing the query and the plurality of potential responses, based on the topic and the type of the query. An obtainer obtains an answer by execution of each of the selected techniques for processing the query and the plurality of potential responses along with an associated confidence score. A determinator determines one of obtained answers as a correct response to the query, based on a comparison between confidence scores associated with the answers.

Determination of a response to a query

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San Jose, CA, United States of America

Tsunghan Wu