Overview of text classification model
[This topic is pre-release documentation and is subject to change.]
Text data volume is growing exponentially in organizations, through channels such as email, documents, social media, and more. This data can carry a lot of valuable information that—when extracted and acted upon—can help you provide better products and services to your customers. Dealing with this ever-growing data can be time-consuming and error prone, and can lead to missed business opportunities and costs.
Text classification is one of the fundamental natural language processing (NLP) problems. It allows tagging of text entries with tags or labels that can be used for sentiment analysis, spam detection, and routing customer requests, just to name a few examples.
Use AI Builder text classification with Microsoft Flow and PowerApps to automate and scale your business processes and free your employees to act on these insights. It can also be used as an input for other AI capabilities such as subscription user churn and predictive analysis. AI Builder can learn from your previously labeled text items, and enable you to classify unstructured text data stored in Common Data Service into your own business-specific categories.