AI has made data mining incredibly easy. Text-understanding AI is a technology that views text and interprets it. Its goal is to understand the text and derive meaning and context from it. Here are some ways it can derive meaning from large sets of text.
Text Analytics
Text analytics AI, sometimes called text mining, can be used to classify, sort, and extract information from the text it’s given. It determines any relationship or pattern in the text. This process allows businesses to speed up business operations, streamlining workflow and improving decision-making. It’s great for processing data from reports, social media comments, documents, and emails.
Four Applications
Text understanding AI has four major applications.
- Text Summarization condenses text and summarizes the crucial information and meaning. It chooses the most important data and phrases and accurately presents the overall meaning. It can be used for long documents such as research reports, HR surveys, and customer reviews.
- Text Categorization, also called text classification, assigns categories to a piece of text data. It associates certain keywords with predefined topics, users’ intentions, or sentiments and then categorizes them. This process allows you to structure, classify, and arrange documents such as research papers, spam emails, patient reports, and more.
- Sentiment Analysis uses algorithms to decipher human emotions and opinions. It’s sometimes referred to as opinion mining or emotion AI. It can tell you if the general feeling of a piece is positive, negative, or neutral. Businesses with large social media followings or many customer reviews can use this tool to determine how customers generally feel without combing hundreds of posts themselves.
- Text Extraction scans a text and pulls out important information such as places, brand names, and product information.
AI can be a great tool for businesses and organizations that need to quickly analyze a large amount of data.