PDF is a multipurpose file format, and this helps it in being used in multiple domains and applications. However PDF documents can also be difficult to work with sometimes. Most users find it difficult to edit documents given the limitations of most PDF viewers. So, if you want to extract data from a PDF document or edit a part of a document, you will likely be unable to do so.
A PDF parser or scraper is an application that identifies the different types of elements in a PDF file and extracts them for your use.
So, how does PDF parser work? A PDF parser goes down to the foundational blocks of a PDF document and uses an algorithm to identify the types of data included in the document. A well-trained PDF parser will be able to identify all basic types of document elements.
A PDF parser should be able to extract all the different types of elements included in a document. In general, the following types of data can be extracted by a PDF parser.
This is the most basic form of data. If a PDF document contains text, you can copy and paste it, but you cannot get away with formatting problems in word processing software. A PDF parser extracts the text with the right formatting so that you can use it as is.
If the PDF is created from a dataset or contains fields with single pieces of data, the PDF parser can accurately extract it for you. It can neatly arrange the data in a particular field according to the field, so you can copy it elsewhere.
Most modern PDF parsers can identify the presence of tables in a document.
This may be counted as significant progress since most old PDF parsers would consider all types of data as paragraphs and make a mess of tables, with users eventually having to copy data manually.
If there are any images present in the PDF document, the PDF parser can extract individual images for you and allow you to save them. This is especially beneficial if you want to recreate images from these documents elsewhere since it saves you the burden of having to take multiple, low-quality screenshots.
A PDF parser is a useful tool to have in your document processing arsenal. It allows you to extract essential data from any PDF and recreate it elsewhere. Especially if you want to extract tables from a PDF, tools like Docsumo’s free table extractor tool can be really useful. Go ahead and see for yourself. It’s completely free with no sign-up required.
In today’s dynamic business world, filing and archiving official documents in the digital form makes it handy, and works wonders in the future or in unforeseen circumstances.
With an automated data extraction solution, loan documents can automatically be processed end-to-end without any human errors and delays. Automation in loan document processing prevents downtimes, eliminates data redundancy, and allows companies to respond faster to client queries. By combining machine learning with deep learning and OCR, companies can eliminate huge costs, derive actionable insights, and streamline loan processing and approvals through efficient data extraction and analysis.
Mortgage lenders receive multiple identity and income verification documents along with different forms from loan applicants in a variety of formats and styles. Traditional OCR solutions fail to extract data from these semi-structured documents and that’s why more and more lenders are adopting intelligent document processing solutions. IDP solutions not only extract data correctly, they are able to validate extracted data against predefined rules in order to improve accuracy.
Intelligent Document Processing is an automation technology that captures information from a myriad of documents and data sources, extract data, and organizes it for further processing. IDP solutions enable businesses to seamlessly integrate with core processes, eliminate manual labour, address challenges faced in reading different document layouts, and meeting legal & compliance requirements. Accurate data is the foundation of every organization, and IDP assists businesses in dealing with the complexity of processing huge volumes of documents, helping them automate manual data entry processes, and move away from traditional semi-automated OCR workflows.