IBM Natural Language Understanding
Analyze text data at scale with AI-powered natural language processing
This API is best for developers looking to integrate natural language processing capabilities into their applications with ease.
Developers would use this API primarily to analyze large amounts of textual data, identifying relevant entities, sentiments, emotions, and other key information for further analysis, data modelling or training of machine learning models. Service is available through RESTful APIs and can be deployed on cloud as well as on-premises. With its out-of-the-box feature sets, the API significantly shortens the development time of NLP-based systems, and reduces the resource overhead required to maintain and scale such systems.
Key features
- Entity recognition
- Sentiment analysis
- Semantic roles labeling
- Concept analysis
- Emotion analysis
- Summarization
- Topic modeling
Potential use cases
- Sentiment analysis of customer feedback: Analyze customer feedback data for positive/negative sentiment and identify areas of improvement in products/services.
- Content summarization: Use the API to generate summarized versions of long-form content such as research papers, articles or legal documents for easy consumption.
- Topic modeling for social media monitoring: Real-time monitoring of social media feeds to identify key topics and their sentiment scores for marketing and branding purposes.
IBM Natural Language Understanding API has been immensely helpful in extracting meaningful insights from our large collection of customer support chats. The ability to identify sentiment trends across the chat history and voice of the customer analysis has helped us improve our support services.
Related Technologies
- Google Cloud Natural Language
- Amazon Comprehend
- Microsoft Azure Cognitive Services