Description: Keyword extraction is the process of identifying and extracting key terms from a text. This process is fundamental in the field of natural language processing (NLP), where the goal is to understand and analyze human language. Keyword extraction allows for summarizing the most relevant information from a document, facilitating indexing and content search. Through algorithms and text analysis techniques, words or phrases that capture the essence of the content can be identified, which is useful in various applications, from search engines to recommendation systems. The relevance of this process lies in its ability to improve efficiency in information management, allowing users to quickly find what they need without having to read lengthy documents. Additionally, keyword extraction is essential for creating automatic summaries and categorizing content, making it a valuable tool in the digital information age.
History: Keyword extraction has its roots in the early developments of natural language processing in the 1950s. As computing advanced, more sophisticated techniques began to be implemented in the following decades. In the 1990s, with the rise of the Internet, the need to organize and retrieve information led to increased interest in keyword extraction. With the development of machine learning algorithms and, more recently, large language models, keyword extraction has significantly evolved, allowing for greater accuracy and relevance in results.
Uses: Keyword extraction is used in various applications, such as search engines, where it helps index content and improve the relevance of results. It is also applied in recommendation systems, sentiment analysis, and in creating automatic summaries of texts. Additionally, it is useful in search engine optimization (SEO) to identify terms that can attract traffic to a website.
Examples: An example of keyword extraction can be seen in tools that extract relevant terms from various types of documents to facilitate searching. Another case is the use of keyword extraction algorithms in data analysis platforms, which help identify trends and topics in large volumes of text, such as in social media or user comments.
