Topic Labeling is an (NLP) Natural Language Processing technique that enables you to automate tagging and organizing massive values of textual data based on the topic or theme.
On a daily basis, businesses generate a large volume of documents and unstructured text such as emails, social media posts, reviews, forum discussions, and customer support tickets. But when it comes to analyzing and making sense of this data, it is far too big to process manually. Even if you go ahead and start analyzing the data manually, it will be too time-consuming and you are bound to make mistakes.
This is where topic labeling can help you out. It can make it much easier and faster to accurately analyze and extract large volumes of data. In this blog, we will discuss what topic labeling is and how you can use it to analyze unstructured text.
What is Topic Labeling?
Topic Labeling is also known as topic extraction is a machine learning and NLP technique that examines and organizes large volumes of unstructured text data. It can tag and categorize documents or even each paragraph based on the topic or theme of the text.
Read the full article here:https://www.bytesview.com/blog/topic-labeling/
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