A mandatory form is a type of form that requires the user to complete one or more fields before submitting it to the server. These fields are usually marked by an asterisk (*) or red font and are often highlighted. Learn how to detect them with Natural Language Processing in this blog post.

What is Natural Language Processing?

Natural Language Processing (NLP) analyzes language form to identify its meaning. It’s a branch of artificial intelligence that can interpret natural language data, such as text. NLP has initially been a research topic in computational linguistics. It is being applied in computer science, cognitive psychology, and human-computer interaction.

Why Use Natural Language Processing to Detect Mandatory Forms?

Natural language processing is a powerful tool that can be used to detect mandatory forms. It’s one of the most common tasks in Natural Language Processing and can be done efficiently using different methods. One such way is using machine learning algorithms to recognize phrases like “is required” or “must provide.” You could also use keyword detection, which looks for keywords or phrases that are typically found on forms, such as “name,” address,” or “email.”

How to Detect Mandatory Forms with Natural Language Processing

Many developers struggle with how to do this and end up with a bold asterisk next to the field name. We need to be able to programmatically detect the mandatory fields by looking at the page’s content.

We’ll first use Natural Language Processing (NLP) on the form code for each field. This will give us a list of all words in each area and their corresponding weights. The more often a word appears, the higher its weight is.

Next, we’ll use these weights to determine what words are most likely missing from fields that have an asterisk next to them or other indications that they’re mandatory. Finally, we’ll filter out all words with weights below a certain threshold and then look for any remaining words that only appear in one field but not another.

Conclusion

Determining mandatory fields is very critical in automated document processing pipelines such as insurance document processing, healthcare document processing, perming document processing. Failure to detect this information at the beginning of the process will cause the process to pause processing documents with missing data. The submitter of the forms needs to be contacted to remedy the situation, which increases the time and the cost to process all documents.  To know more how we can help, visit www.deepdatum.ai.