“INFORMATION EXTRACTION FROM UNSTRUCTURED DATA”
Date
2023-04-30
Journal Title
Journal ISSN
Volume Title
Publisher
I.O.E. Pulchowk Campus
Abstract
In today’s digital age, the digitization of paper documents like invoices and receipts
has taken on more significance. Nevertheless, manually entering data from these
papers can take a lot of time and be prone to mistakes, which causes inefficiencies
and drives up expenses for enterprises. To solve this issue, we created a software
platform that automates the process of collecting important data from scanned
documents using deep learning technology, more specifically the LayoutLM architecture.
Users can upload their scanned papers in bulk to our platform and
choose which fields, including date, merchant name, and total amount, they want
to extract. The technology is scalable and can manage high document volumes
while preserving precision and effectiveness.The user-friendly interface makes it
easy for users to upload and extract information from their scanned documents.
Our platform offers significant benefits, including increased efficiency, accuracy,
and cost savings, and has the potential to transform the way businesses handle
physical documents. In this project, we will provide an overview of our software
platform, including the technology behind it, its key features, and its potential
applications.
Description
Even though everything seems to be going digital, many of the information conveying
between parties happen in hard copy. As the use of computer to process
data is increasing day by day, the process of manually extracting information from
documents can be time-consuming, error-prone, and expensive.
Keywords
Intelligent Document Processing,, Key Information Extraction,, Deep Learning