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Research Paper | Computer Science & Engineering | India | Volume 8 Issue 3, March 2019 | Popularity: 6.3 / 10
Improved Information Extraction with NLP & CRF for Invoices
Monalin Pal
Abstract: In a general Invoice processing system, the process starts from manually uploading the different format of invoices like paper, pdf, excel, document, image etc. for handling a supplier invoice, from its receipt to upload in the ERP system and is ready for payment. This invoice process is manually handled for any organization. Each process of manual upload and payments was time consuming. This is an attempt to use AI in invoice processing system, where we can process invoices automatically by extracting the relevant information from the invoices and feeding it to the ERP systems through RPA (Robotic Process Automation). This process will help to reduce costs while improving both the accuracy and the speed of data extraction. Invoice Processing Advisor that can read invoice and extract the accurate information in a representable format. Annotations and Machine Learning for data extraction from the preprocessed data. Intelligent Invoice Processing will help to cater the increasing business needs as we see that majority of organizations spend lot of man FTEs and time for processing invoices. With the help of AI, this solution will be helpful to extract the information from the invoices more accurately and reduce the manual effort as well as the cost. We can easily scale it to multiple type of invoices as well introduce various business rules check that can communicate with the RPAs to perform any type of complex actions.
Keywords: Artificial Intelligence, CRF Model, Natural Language Processing, Python
Edition: Volume 8 Issue 3, March 2019
Pages: 1237 - 1239
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