Semantic flexibility and approximation are a fundamental part of intelligent behavior that semantic applications are expected to deliver.
The Amtera Semantic Relatedness API
provides an easy-to-use service, which supports applications accessing a large-scale distributional knowledge base. The API’s core operation is to calculate the semantic relatedness between pairs of text excerpts based on the likeness of their meaning or semantic content. By incorporating semantic approximations and disambiguation functionalities, Amtera can differentiate between a movie star and a star cluster or galaxy.
The service is optimized to support the high throughput needed for industry applications. Currently the service is available in…
We are proud to be part of the first Publishing Hackathon
! The organizers of the Publishing Hackathon are inviting designers, engineers, programmers, an entrepreneurs to spend 36 hours together in teams to developer a new approach to digital book discovery.
The Publishing Hackathon will take place on May 18th and 19th at The Alley NYC, the leading digital co-working space in New York. The participants will be briefed by a cross-section of book publishing leaders, and then will form teams to create apps, websites, programming or businesses that can address the issue of book discovery in this rapidly evolving…
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.
Wikipedia defines Machine Learning
as “a branch of artificial intelligence that deals with the construction and study of systems that can learn from data.”
(If you arrived here looking for how to add or list an API to Mashape, you check out the Tutorials section here
Below is a compilation of APIs that have benefited from Machine Learning in one way or another, we truly are living in the future so strap into your rocketship and prepare for blastoff.
OCR recognition service
– Ocrapiservice.com is an cloud based optical recognition engine. We take images as input and we reply…
Jacob Perkins, author of Python Text Processing with NLTK 2.0 Cookbook, and creator of Python NLTK Demos and APIs, recounts in this post
how he got started in building APIs, and before his discovery of Mashape:
I wasn’t sure if anyone would actually use the API, but I knew the best way to find out was to just put it out there. So I did, initially making it completely open, with a rate limit of 1000 calls per day per IP address. I figured at the very least, I might get some PHP or Ruby users that wanted the power…
, with its mission to provide users with fast and complete answers, has published 7 APIs on Mashape, with a freemium usage model.
– Lets you retrieve public proxies
– Gives you access to the keyword data
– Gives you access to millions of entities; cities, etc
– Find answers to natural language questions
– Lets you process web pages
Text Processing API
– Processes natural language text
– Searches the WebKnox Web Index and news results.