Are you trying to find a tool to perform text classification easily? We have the best recommendation for you!
The practice of categorizing or grouping text data into categories is known as text classification. A key component of natural language processing, it plays this role. We are surrounded by text in the digital world we live in, whether on our social media accounts, in advertisements, on websites, in Ebooks, etc. Since most of this text data is unstructured, categorizing it can be quite helpful.
Text categorization mainly entails organizing text-based digital material into themes in an attempt to bring some sort of order to the enormous amounts of data spread over the internet.
Moreover, this is made possible by advanced AI that employs methods of natural language processing.
Text Classification has many possibilities of applications. Some widespread uses are:
Spam detection in emails
Sentiment analysis of online reviews
Labeling documents based on topic like research papers
Language detection like in Google Translate
Age/gender identification of anonymous users
Tagging online content
Speech recognition used in virtual assistants like Siri and Alexa
Approaches
You can achieve text classification with three main tactics:
Rule-based approaches
These methods use individually created language rules to categorize content. Making a list of words associated with a particular column and classifying the text according to how often these words appear is one method of grouping text. For instance, phrases like “fur,” “feathers,” “claws,” and “scales” could aid a zoologist in locating internet texts discussing animals. These methods take a long time to develop, need a lot of domain expertise, and are challenging to scale.
Machine learning approaches
We can use machine learning to train models on large sets of text data to predict categories of new text. To be able to train models feature extraction is the process of converting text data into numerical data. Bag of words and n-grams are two crucial feature extraction strategies.
Hybrid approaches
These strategies combine the two previous algorithms. They create a classifier that you can adjust depending on the situation by combining rule-based and machine learning techniques.
If you want a tool to perform text classification that’ll be good for your business you need to try:
Why is our recommendation Text Classification IAB Taxonomy?
Text Classification IAB Taxonomy is the best IAB Taxonomy content classifier. Not only is it extremely accurate, but you can also quickly organize your data using its classification.
Texts are categorized using the IAB Taxonomy classifier into one of 360 subjects. The primary category (such as sports, business, or science) and subcategories make up its two levels of depth (soccer, agriculture or physics). It is based on the Taxonomy of the IAB Quality Assurance Guidelines.
What are the most common uses cases of this API?
This API is meant to assist businesses that have a lot of data that has to be categorized. By categorizing the text, you can collect it. This is also ideal for marketing agencies.
Also, helpful to classify sentences or slogans, you will be given the exact categorization in IAB standards.
Also published on Medium.