Watson Natural Language Understanding (NLU) is a service composed of a collection of text analysis functions that derive semantic information from content. You can input text, HTML, or a public URL, and leverage sophisticated natural language processing techniques to get a quick high-level understanding of your content and obtain detailed insights.
With Natural Language Understanding (a new rendition of the Alchemy Language API which has been deprecated), developers can analyze semantic features of text input, including categories, concepts, emotion, entities, keywords, metadata, relations, semantic roles, and sentiment. All developers have to do is to call a REST API within their application.
But organizations keep asking "What can I do with the Natural Language Understanding service?", " What are practical applications that can leverage the capabilities of this Watson API?".
Here is a list of use cases that can be implemented with the Natural Language Understanding service:
- Social sentiment analysis
Have you ever seen those dashboards that depicts how good or bad your brand or a certain product is doing in the market based on Facebook posts or Tweets? To build these dashboards, you need to understand the sentiment towards your brand or product conveyed in the text of those posts or Tweets. You can used the targeted sentiment feature in the Natural Language Understanding service to accomplish this goal.
Do you have a bunch of documents to order and categorize according to their content? Well, by using the Natural Language Understanding categories feature you don't have to read them at all. This service will read the document for you and return the appropriate categories.
If you are training a chatbot by reading emails or web pages to figure out how the bot should be able to respond, stop wasting your time. Use the Natural Language Understanding keywords feature to read through emails or web pages for you and extract all the relevant.
If your organization is working on having a virtual assistant or already has one, the use of this NLU feature is a must. The emotion feature provides the ability to understand how your interlocutor is feeling. As the user’s emotions change, so should your answer in order to keep pace or try to influence the user’s mood in a positive direction.
The Watson Natural Language Understanding service is very easy to use and really powerful. To help developers get started quickly with this service I wrote the IBM Redbooks publication Building Cognitive Applications with IBM Watson Services: Volume 7 Natural Language Understanding. This book covers the following topics:
- Basics of Natural Language Understanding
- Creating a Natural Language Understanding service in Bluemix
- An example use case with working code in GitHub
Enjoy and have fun using the Natural Language Understanding service!
Sebastian Vergara is an Expert Certified Architect in IBM Sales & Distribution, IBM Uruguay. His areas of expertise include cloud computing, DevOps, Design Thinking, and cognitive computing. He has over 8 years of experience in the IT industry. Sebastian led several projects to design and build cognitive solutions, such as the development of a transactional virtual assistant for an international bank and a cognitive chatbot for a major pharmaceutical company in Latin America that uses Watson Natural Language Classifier, Text to Speech, Natural Language Understanding, Visual Recognition, and other Watson technologies. Sebastian teaches at the Engineering College in the Universidad de la República Uruguay (UdelaR) where he introduces students to architecture and design, integration, cloud computing, and trending technologies.