After we posted the list of NLP
, Sentiment Analysis
, and Machine Learning
APIs a while ago, we noticed that some API descriptions require a little bit of digging into, to fully appreciate what these APIs can do. Here’s an example:
Text analysis API including wordnet synsets,relation extraction,named entity recognition and classification,lemmatization,part of speech tagging,tokenization, and semantic role labeling.
If you’re not familiar with these words, you could totally miss the features that this API
is capable of.
To help with that, we have listed below an explanation to some of these words in the NLP/Machine Learning context; as…
Just a few days back we posted a List of 50+ Machine Learning APIs
Note: Check out our latest API collections page for the list of updated APIs.
The APIs below are a Sentiment Analysis subset group from that Machine Learning API list. Sentiment Analysis
refers to “the application of natural language processing, computational linguistics, and text analytics to identify and extract subjective information in source materials.”
We hope you’ll it find useful!
Sentiment analysis, stemming and lemmatization, partofspeech tagging and chunking, phrase extraction and named entity recognition.