Automatic document classification is one of the main activities for effectively managing text and unstructured information.
Also referred to as categorization, clustering or text classification, automatic document classification allows you to divide and organize text based on a set of predefined categories that allow rapid, easy retrieval of information in the search phase.
Automatic document classification: what is it and how does it work?
But what is the process by which you assign a text to the proper category of reference? First, this requires understanding the meaning and context of words in the most precise manner possible. Take the word “apple” for example. The process must be able to distinguish whether the text is referring to the fruit, the computer or the company. To do so, you must be able to interpret the meaning of the text and correctly identify the relationships between concepts.
Here you can find further information about content classification tools.
Do i really need document classification? Isn’t Google enough?
But is it really necessary to organize text into categories if Google is able to find (almost) everything you need? Used for certain tasks, such as defining a word, learning more about concept, searching for a well known public document or the latest news, Google can usually provide what we need in just a few clicks from reliable sources. However, when the task involves business-specific contexts that are much more complex, the situation changes completely. Here, without a systematic or purposeful document classification on the content of your interest, finding the content you need will be much more difficult, and simply Googling your search will likely be a waste of time.
The limits of manual approaches: why automatic document classification is necessary
While manual document classification may be highly detailed and accurate (possible only by human intelligence), it will inevitably suffer from two major limitations that make it impractical: it takes a lot of time and it is subjective.
The amount of time required to organise text in categories is directly proportional to the quantity of text. Take for example of the volume of content on a corporate intranet, all of the articles in a newspaper’s archive, the full regulations and laws of a governmental institution or even all of the information on the web that could be useful for a company’s business—it is inconceivable that humans could manage this volume of information in a reasonable timeframe.
Even so, humans, with our biases and different interpretations of reality, will pass these on to our text classification, resulting in inconsistent, subjective and even incorrect classification.
This is where automatic document classification comes into play. Faster, scalable and objective, it allows businesses and organisations from any sector efficiently organise content, making it available at any moment.
Automatic document classification: best practices for getting started
Many believe in a perfect algorithm, one that can automatically classify documents with little initial set up, and immediately return high-quality results for every area of application. Unfortunately, no software can function well, much less independently, with just a few examples. Instead, reliable automatic document classification software requires that we start from the beginning:
–Define the requirements for organising content and based on this, you will decide how the content should be organised.
–Define the method: Start with a clear, objective configuration of the categories and classification rules and then conduct testing, customization and refinement activities.
The more time, care and attention that you invest in these initial phases, the more likely you’ll be to get results that, while perhaps not perfect, will provide great value to your company.