To be future-proof, companies need to embrace automated labelling. But where to start? In this blog series, we focus on content metadata. A few weeks ago, we discussed keyword extraction. Today, we'll have a closer look at a related label: topic classification.
What is topic classification?
Topic classification comes with an aggregated label. The main difference with keyword extraction is that it's broader in nature — once you have a collection of keywords, you can consider the overarching topic. Logically, the term attributed to this label will be a bit more general.
Unlike keywords, topics are always related to a taxonomy people can recognise. Their labels aren't random. For example, if a piece of content is about soccer, the associated label will fit into an existing taxonomy.
Why use automated labelling?
Remember the genre stickers on library books that helped you navigate the collection? Topic classification is the highly detailed version of this concept. As it enables you to classify and structure content using a taxonomy, it will facilitate distribution and make materials more accessible. Teachers and students can easily find what they're looking for.
And once you're ready to take things up a notch, you can. As a publisher, you'll want to cover all topics in a taxonomy. Topic classification makes it easy to analyse whether there are any gaps to fill. You can walk through your own 'digital library' and instantly spot the 'empty bookcases,' which you can then start to fill by creating new content.
Automated labelling: how to go about it?
Like other content metadata, topic classification requires you to train an AI model based on labelled teaching materials. The difference is that you need to include the taxonomy in the model. Whereas keywords are practically unlimited, topic classification is finite because it represents a specific domain. It is linked to an existing structure (a taxonomy), which means it comes with a smaller set of labels.
Benefits of automation
If you create labels manually, it will take a lot of time and effort. Automation results in significant savings. At the same time, information becomes more accessible, and people will find the content they're looking for faster.
Want to know what other labels you can use for educational purposes? Keep an eye on our next blog post to read more about learning objectives tagging.
