公开(公告)号：US11501549B2

公开(公告)日：2022-11-15

申请号：US16917572

申请日：2020-06-30

申请人： ACCENTURE GLOBAL SOLUTIONS LIMITED

发明人： Sawani Bade ,  Srinivasan Ponpathirkoottam Raghavan ,  Samatha Kottha ,  Shruti Chhabra ,  Praneeth Medhatithi Shishtla ,  Debayan Chakraborty ,  Sreerekha T. V. ,  Himani Bhatt ,  Amit Nandi ,  Akanksha Juneja ,  Soubhagya Ranjan Mohapatra ,  Ashok Kumar Shivarajan ,  Kedar Bhat ,  Karthick Selvamuthukumaran

IPC分类号： G06F30/00 ,  G06V30/413 ,  G06F40/284 ,  G06V30/412 ,  G06V30/414

摘要： A hybrid rule-based Artificial Intelligence (AI) document processing system processes a non-editable document with at least one invoice to accurately extract data from tables in the invoices. The non-editable document is preprocessed for conversion into a markup format and pages including the invoice are identified. The invoice is processed via a document process by parsing the pages in different directions to generate a first set of predictions and via a block process wherein logical information blocks from the invoice are processed to generate a second set of predictions. The missing entries from a selected table are identified by applying rules to the first set of predictions and the second set of predictions. Any discrepancy between the missing entry values between the first and second set of predictions are resolved and the resulting data is exported to downstream systems for further uses.

公开(公告)号：US11495227B2

公开(公告)日：2022-11-08

申请号：US16990460

申请日：2020-08-11

申请人： ACCENTURE GLOBAL SOLUTIONS LIMITED

发明人： Sawani Bade ,  Himani Bhatt ,  Debayan Chakraborty

IPC分类号： G10L15/22 ,  G06N5/04 ,  G06N5/02 ,  G06F16/25 ,  G06F40/205 ,  G06F16/28 ,  G10L15/26 ,  G06F40/289 ,  G06F16/2452

摘要： An Artificial Intelligence (AI) based user intent analyzer system analyzes a received user query to determine an intent of the user query and enables execution of processes on a backend system based on the user intent. The user query is divided into a plurality of portions and the portions with extraneous information are discarded. The remaining portions are parsed with a plurality of parsers. The output from the plurality of parsers is processed for extraction of the entities, entity attributes, verbs, and verb arguments. The entities and verbs are further filtered using knowledge graphs and the remaining entities and verbs are mapped to sub-intents using intent mapping rules retrieved from the knowledge graphs. The sub-intents are mapped to the final intent using process rules associated with the process to be executed by the backend system in response to the user query.