Text analysis is the process of derivation of high end information through established patterns and trends in a piece of text. Using cutting edge techniques of Deep Learning like LSTMs, Transfer Learning, etc. our Text Analysis APIs perform significantly better than traditional NLP techniques.
Combine our Text Analysis APIs to solve complex problems such as building chatbots, social media analytics, process automation, etc.
Text Classification can be useful in understanding customer behaviour by categorizing conversations on social networks, feedback and other web sources. Search engines, newspapers, or e-commerce portals categorize their content or products to facilitate the search and navigation.
Semantic Analysis API helps users cluster similar articles by understanding the relatedness between different content and streamlines research by eliminating redundant text contents.API can help bloggers, publishing and media houses to write more engaging stories by retrieving similar articles from past quickly, and news aggregators to combine similar news from different sources to reduce clutter in the feeds of their readers.
Sometimes the three classes of sentiment (positive, negative and neutral) are not sufficient to understand the nuances regarding the underlying tone of a sentence. Our Emotion Analysis classifier is trained on our proprietary dataset and tells whether the underlying emotion behind a message is: Happy, Sad, Angry, Excited or Indifferent.
Find the relevant entities in the references of any journal which can lead to better search experience of the researchers.
Extract linguistic features like part-of-speech tags and dependency labels in raw, unstructured text.