Document Classification | Knowledge Base | Definition

 

What Is Document Classification and How Does It Work?

Document Classification organizes documents by type, assigning a document to a group. To classify documents, document classification automation uses either or both of two major types of data stored within documents: text-based information and visual-oriented information. Text is easy to understand. Visual information can be pictures, presence of logos or other visually-distinct information such as data structured in a tabular format. The most common type of document classification is a rules-based approach where a subject matter expert identifies words that are unique to each document type. From there, rules are encoded that dictate document class assignments based on the presence of one or more of these words. The benefits are that rules-based approaches are fairly straightforward to understand and create. The drawbacks include the amount of time required to analyze and construct the rules as well as the potential that words identified as belonging to one document class might also belong to another. This creates the potential for errors.

A more modern approach to classifying documents using text uses a machine learning algorithm that operates on the text to automate the process of identifying words or phrases that are distinctive enough to determine the proper document class. These algorithms identify textual “features” that can go beyond what most humans can identify, and they can operate on a much larger data set to provide more comprehensive coverage. The actual type of machine learning algorithm used is not relevant provided the performance is suitable to the need. In some cases, multiple algorithms or techniques are used depending upon the nature of the information.

The benefits are that the investment in time and effort to construct rules is removed and replaced by “compute time” with significantly more data going into analysis to ensure that automation can be more comprehensive. The drawback is machine learning can be a black box with little visibility into the process yielding the results.

Another means to classify documents is to use the visual information available. This type of classification requires algorithms based on computer vision that enable it to identify key visual features of a document to sort one document type from another. Often, especially with visually-distinct document classification projects, visual classification does not require use of OCR, which can be a time-consuming process.

Document Classification Automation

Document Classification Techniques - A Business Primer

Explore the traditional and the newest document classification techniques from rules-based classification to cognitive classification with the associated use cases in this eBook. Classification and separation of documents is critical for many business processes from mortgage processing to accounts receivable. Regardless of whether a process is key to revenue generation or a supporting function, the need to effectively and efficiently manage, classify and organize documents to support a given process becomes more challenging as the complexity and volume of data increases. Organizations are looking to better classify and group documents to:

  • Sort and separate incoming documents to facilitate specific business processes.
  • Identify documents that are governed by regulations requiring proper retention.
  • Identify documents that are part of a legal action.
  • Prevent certain documents (or data contained within them) from being shared outside of the organization.

This eBook discusses the various document classification techniques, their strengths and weaknesses use cases.

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