Keyword extraction (also known as keyword analysis) is a technique that automatically identifies and extracts the words that best describe the subject of a document. It helps summarize the content of a text and recognize the main topics.

Why is Keyword Extraction helpful?

Imagine you need to analyze dozens of textbooks as part of a curriculum. Keyword extraction technique will sift through the whole set of data in minutes and obtain the words and phrases that best describe each subject. This way, you can easily identify which parts of the available data cover the subjects you are looking for while saving your teams many hours of manual processing.

Keyword extraction is about automatically finding what’s relevant in a large set of data.

Keyword extraction may be the key to finding relevant keywords within massive sets of data (like books, articles, papers, or journals) without having to actually read the whole content. You can use a keyword extractor to pull out single words (keywords) or groups of two or more words that create a phrase (key phrases). But it also works the other way around; keyword extraction will enable easy search and retrieval of content on topics, keywords, (learning) objectives and readability levels..

What is what?

The realm of keyword extraction is complex and one can easily be overcome with confusing terminology. ‘Key phrases’, ‘key terms’, ‘key segments’ and ‘keywords’ for instance are the terminology used for defining the most relevant information contained in a document. Although the terminology is different, the function is the same: characterization of the topic discussed in a document.

Keyword extraction methods can be roughly divided into:

Keyword assignment

Choosing keywords from a list of controlled vocabulary or taxonomy.

Keyword extraction

Keywords are chosen from words that are explicitly mentioned in an original text.

Methods for automatic keyword extraction can be:

Supervised

Usually require a large human-annotated corpus to train the model.

Unsupervised

Based on word graph networks and or machine learning.

Unsupervised methods can be further divided into simple statistics, linguistics or graph-based, or ensemble methods that combine some or most of these methods.

Semi-supervised

A combination of the above.

3 advantages of Keyword Extraction

Thanks to keyword extraction, organisations are able to automate some of their most routine tasks, saving valuable time and resources while analyzing data. Businesses can also use keyword extraction to get valuable insights about their products or services and use them to make data-driven decisions.

1] Scalability

Automated keyword extraction allows you to analyze as much data as you want. Yes, you could read texts and identify key terms manually, but it would be extremely time-consuming. Automating this task gives you the freedom to concentrate on other parts of your job.

2] Consistent criteria

Keyword extraction acts based on rules and predefined parameters. You don’t have to deal with inconsistencies, which are common when performing any text analysis manually.

3] Real-time analysis

You can perform keyword extraction in real-time, and get insights about how learners interact with your learning materials

Not all Keyword Extraction is created equal

Keyword Extraction is not a unified domain of research. In spite of the existence of many approaches in the field, there is no single approach that (effectively) extracts keywords from different data sources. As a consequence, there are many approaches to keyword extraction and a growing number of distributors of keyword technology. Finding the right solution for your demands in this vast landscape can be quite a challenge.

EDIA focuses on educational publishing and has trained its AI models using both generic textual content and textual content used in education. With over 15 years of experience in this domain, we are well equipped to give you all the necessary advice and support in a form of a personal consultation or workshop identifying your content management needs and building a business case for smart content and metadata use, such as keyword extraction.

What is Keyword Extraction?