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AYLIEN
AYLIEN

7
13
+ 1
0
rasa NLU
rasa NLU

26
36
+ 1
10
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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
  • python
  • NLP

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.

- No public GitHub repository available -

What is AYLIEN?

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.

What is rasa NLU?

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.
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        What are some alternatives to AYLIEN and rasa NLU?
        SpaCy
        It is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. It comes with pre-trained statistical models and word vectors, and currently supports tokenization for 49+ languages.
        Google Cloud Natural Language API
        You can use it to extract information about people, places, events and much more, mentioned in text documents, news articles or blog posts. You can use it to understand sentiment about your product on social media or parse intent from customer conversations happening in a call center or a messaging app. You can analyze text uploaded in your request or integrate with your document storage on Google Cloud Storage.
        Amazon Comprehend
        Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to discover insights from text. Amazon Comprehend provides Keyphrase Extraction, Sentiment Analysis, Entity Recognition, Topic Modeling, and Language Detection APIs so you can easily integrate natural language processing into your applications.
        Gensim
        It is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Target audience is the natural language processing (NLP) and information retrieval (IR) community.
        Wit
        Wit enables developers to add a modern natural language interface to their app or device with minimal effort. Precisely, Wit turns sentences into structured information that the app can use. Developers don’t need to worry about Natural Language Processing algorithms, configuration data, performance and tuning. Wit encapsulates all this and lets you focus on the core features of your apps and devices.
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