Natural and unstructured language is how humans largely communicate. For this reason, it’s often the format of organizations’ most detailed and meaningful feedback and market intelligence.
Historically impractical to parse at scale, natural language processing has hit mainstream adoption. The global NLP market is expected to grow 20% annually through 2026. Analysts suggest that
As a benchmark-topping natural language processing API provider, Diffbot is in a unique position to survey cutting-edge NLP uses. In this paper, we’ll work through the state of open source, cloud-based, and custom NLP solutions in 2021, and lay out four ways in which technical leaders are structuring text to drive data transformations.
In particular, we’ll take a look at:
- How researchers are using the NL API to create a knowledge graph for entire country
- How the largest native ad network in finance uses NLP to monitor topics of discussion and serve up relavent ads
- The use of custom properties for fraud detection in natural language documents at scale
- How the ability to train recognition of 1M custom named entities in roughly a day helps create better data