Fast Scalable Natural Language Understanding Solution
Use Cases and Deployment Scope
We are using IBM Watson Natural Language Understanding in two projects. [In] the first one, we use it to find important concepts and keywords in a paragraph and then we use this information to generate questions asking about these important concepts and keywords. In the other project, we are using IBM Watson Natural Language Understanding along with IBM Watson Assistant to rephrase and summarize what the chatbot user has said.
Pros
- Easy to use and extensive APIs.
- Decent accuracy.
- It recognizes concepts and semantic roles.
Cons
- Improve Sentiment Analysis accuracy.
- Prevent having conflicting results (sad and happy, etc.).
- Foreign names detection.
Likelihood to Recommend
IBM Watson Natural Language Understanding is a Swiss Army knife that can be used in many scenarios. An extensive list of easy to use APIs is provided making it very easy to integrate it in any environment. The text analysis is decent and above market average. It generates results in many forms to suit may scenarios (important keywords, concepts, sentiment analysis, etc.).
