Kimono vs rasa NLU
Overview
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CLI (Node.js)
Manual
Detailed Comparison
You don't need to write any code or install any software to extract data with Kimono. The easiest way to use Kimono is to add our bookmarklet to your browser's bookmark bar. Then go to the website you want to get data from and click the bookmarklet. Select the data you want and Kimono does the rest. We take care of hosting the APIs that you build with Kimono and running them on the schedule you specify. Use the API output in JSON or as CSV files that you can easily paste into a spreadsheet. | 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. |
Build an API in seconds with kimono to power your apps, models and visualizations with live data without writing any code;The kimono smart extractor recognizes patterns in web content allowing you get the data you want quickly and visually;We host your APIs and data in the cloud and run them on the schedule that's right for you;We serve up cached data even if the source URL is down or the extractor fails;App builder lets you create responsive web apps on top of your APIs without writing any code | Open source; NLP; Machine learning |
Statistics | |
Stacks 17 | Stacks 120 |
Followers 36 | Followers 282 |
Votes 5 | Votes 25 |
Pros & Cons | |
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Integrations | |
| No integrations available | |
What are some alternatives to Kimono, rasa NLU?
import.io
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ParseHub
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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.
ScrapingAnt
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Octoparse
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Speechly
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BeautifulSoup
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Apify
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MonkeyLearn
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Jina
It is geared towards building search systems for any kind of data, including text, images, audio, video and many more. With the modular design & multi-layer abstraction, you can leverage the efficient patterns to build the system by parts, or chaining them into a Flow for an end-to-end experience.
