Text Classification
Text classification is the process of assigning tags or categories to text according to its content. It’s one of the fundamental tasks in Natural Language Processing(NLP) and has a very broad applications including sentiment analysis, topic labeling, spam detection, and intent detection.
Unstructured data in the form of text is everywhere: web pages, social media, emails, chats,survey responses, support tickets, and more. Text is said to be an extremely rich source of information, but extracting insights from it can be hard and time-consuming due to its unstructured nature. Businesses today, are turning to text classification for structuring text in a fast and cost-efficient way to enhance decision-making and automate processes.
In this section, we will be answering some basic questions like: What is text classification? How does text classification work? What are the algorithms used for classifying text? What are the most common business applications?
1. What is Text Classification?
Text classification, also known as text categorization or text tagging, is the task of assigning a set of predefined categories to unstructured text. We use text classifiers to organize, structure, and categorize almost everything. For example, news articles can be organized by topics, support tickets can be organized by urgency, chat conversations can be organized by language, brand mentions can be organized by sentiment, and so on.
As an example, take a look at the following text below:
“The user interface is quite straightforward and easy to use.”
A classifier can take this text as an input, analyze its content, and then and automatically assign relevant tags, such as UI and Easy-to-use that represent this text.
2. How Does Text Classification Work?
Text classification can be done in two different ways: manual and automatic classification. For manual classification, a human annotator interprets the content of text and categorizes it accordingly. This method usually can provide quality results but is very time-consuming and expensive. Automatic classification applies machine learning, natural language processing, and other techniques to automatically classify text which is a faster and more cost-effective method.
Approach to automatic text classification can be grouped into three types of systems:
- Rule-based systems
- Machine Learning based systems
- Hybrid systems
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