There is no doubt that the concept of Natural Language Generation has become one of the constants in the field of Artificial Intelligence, and therefore you have to make sure that you take the appropriate steps to keep pace with this scientific development.
The importance of NLG lies in the endless possibilities of its use. As long as you have information, you need to turn it into useful and more comprehensive information.
Now, let’s talk about the most important NLG examples and applications:
1. Content Creation
One of the most important Natural Language Generation examples is to generate high quality content, such as product descriptions, internal communications, agreements and contracts, marketing and financial reports and many other similar forms of text communication. NLG makes sure all the spelling, grammar and structure are correct.
2. Analytics Dashboards
The data produced by the analyses can be interpreted using NLG-powered tools to produce clear and thorough reports based on the data gathered. This facilitates quick and efficient decision-making.
The chatbot communicates with users using sophisticated natural language processing tools and the capacity to produce effective natural language, which helps automate many crucial everyday business processes.
4. Internet of Things
One of the most important Natural Language Generation examples is its application in the field of the Internet of Things. It can be integrated into the IoT infrastructure to automatically get status reports, maintenance updates, and other system analytics written in plain language, improving responsiveness and preventing a great deal of money from being wasted.
5. Automated Personalization
NLG applications can be used to customize communications between two parties in any business, where marketers can customize chatbots, voice response systems and SMS messages to get the most out of their marketing plans.
6. Health Care
Flexible communication between medical professionals and patients is crucial. We need to use NLG to create a comprehensible language that is simple for the recipient to read and deal with because patients frequently cannot understand the medical phrases that are technically and arranged in the health institution’s databases.
Imagine that you need to generate a product description in an e-commerce store that contains thousands of products, each one different from the other with its own set of specifications. In reality the task would seem impossible, but with NLG this can be done in a short time and with very high quality results.
8. Banks and Insurance
A great Natural Language Generation example is to create automated reports on customer assets: stocks, indices, and portfolios which change every second, then automate it and even personalize reports and enrich them with context-based analysis results.
9. Tourism and Real Estate
Every destination has metadata, as well as hotels, rooms, homes, and offices. This data is transformed by NLG into text that can be easily understood. Without any effort, relevant content can also be automatically updated on websites, advertisements, or digital displays.
10. Human Resources
HR departments need a lot of time to create job references, job descriptions, job profiles, etc. NLG systems generate understandable and attractive text from structured data to be automatically published in all appropriate channels.
In fact, the above Natural Language Generation examples are just a few of endless possibilities of its use. As long as you have data, you can turn it into useful information. And here’s our guide on What is Natural Language Generation