Mediaboss Marketing

It is hard to classify documents. At least manually.

Imagine this: you head into a standard bookstore where pieces are supposed to be classified as genres like thriller, romance, science fiction, and more. You want to pick Andy Weirs Hail Mary a novel with thriller/mystery and science fiction elements.

While the book choice seems on point, the question is: which genre should you head towards? The book can be on the science fiction shelf or on the thriller counter. It can be anywhere. And that is when the manual document classification becomes troublesome.

Sweating already? Fret not, as machine learning is here to help. Not to throw shade at the manual document classification, but they can be tedious if you plan on looking at a world outside books including inventories and databases.

Yet, document classification with machine learning can be a game changer, courtesy of the relevant and available technologies like NLP, Robots, Sentiment Analysis, OCR, and more.

Lets take a deeper dive into all of these.

Simply put, document classification is the automation process where relevant/classifying documents are stacked into relevant classes or even categories.

Often regarded as one of the sub-domain of text classification, an oversimplified version of document classification means tagging the docs and setting them right into predefined categories for the purpose of easy maintenance and efficient discovery.

In hindsight, the process is simple. Its all about extracting and retrieving information. Yet, due to the sheer size of data sets, companies often need to rely on deep learning and machine learning technologies to get ahead of document classification, albeit with a focus on speed, accuracy, scalability, and cost-effectiveness.

And just to mention, document classification can be considered a sub-domain of IDP or intelligent document processing. But more on that later.

As for the approach, document classification takes the text and visual classification techniques into consideration primarily for analyzing the document-specific phrases and also the visual structure.

Visual and text classification can help companies classify every kind of document (stills, pictures, large data modules, and more) with ease.

Short story: intelligent models scan through structured, unstructured, and even semi-structured documents to match them with the corresponding categories.

Long story: The following machine learning techniques are put to use for classifying documents according to categories:

Regardless of the approach, businesses need to find a good way to classify documents as going manual can be time-consuming, erroneous, and obviously hard.

However, if you are looking for broader shades in regards to the process, here are the steps associated with an automated and efficient document classification process:

Theoretical discourse is all cool, but what about the use-cases for document classification. We have it all sorted for you.

Opinion Classification: Businesses use this feature to segregate positive reviews from negative ones.

Spam Detection: Have you ever thought about how your email provider separates standard emails from spam emails? Well, document classification is the answer.

Customer support classification: A random day in the life of a customer support executive can be stressful. Document classification helps them understand the tickets better, especially when the request volume far exceeds their patience.

In addition to the mentioned use cases, document classification can also be used for social listening, document scanning, and even object recognition.

Every organization is information-dependent. Yet, every kind of information isnt meant for everyone. This is the reason why document classification becomes all the more important helping organizations collect, store, and eventually classify details as per requirements. And if you are still a manual evangelist, remember one thing: automation is the key to the future.

About the author: Vatsal Ghiya is a serial entrepreneur with more than 20 years of experience in healthcare AI software and services. He is the CEO and co-founder of Shaip, which enables the on-demand scaling of our platform, processes, and people for companies with the most demanding machine learning and artificial intelligence initiatives. Linkedin: https://www.linkedin.com/in/vatsal-ghiya-4191855/

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What is document classification, and how can machine learning help? - Robotics and Automation News