AYLIEN vs rasa NLU: What are the differences?
Developers describe AYLIEN as "Text Analysis API package consisting of eight different Natural Language Processing, Information Retrieval and Machine Learning APIs". At the top of each mountain of data lies a nugget of invaluable knowledge, but it takes an incredibly powerful tool to bring that mountain to its knees. That's precisely what our Text Analysis API does. On the other hand, rasa NLU is detailed as "Open source, drop-in replacement for NLP tools like wit.ai". rasa NLU (Natural Language Understanding) is a tool for intent classification and entity extraction. You can think of rasa NLU as a set of high level APIs for building your own language parser using existing NLP and ML libraries.
AYLIEN and rasa NLU can be primarily classified as "NLP / Sentiment Analysis" tools.
Some of the features offered by AYLIEN are:
- The first step in understanding a document is to strip it of unnecessary elements. Article Extraction strips HTML documents of ads, navigation elements, and anything that gets in the way of understanding the text.
- Why use 100 words when 10 will do? Summarization extracts key sentences from a text, leaving only the most important concepts.
- Because a text includes more than just concepts, Entity Extraction lists organizations, phone numbers, currency amounts, even individuals mentioned in a text.
On the other hand, rasa NLU provides the following key features:
- open source
rasa NLU is an open source tool with 5.76K GitHub stars and 1.7K GitHub forks. Here's a link to rasa NLU's open source repository on GitHub.