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Keyword Extraction

Looking for the keyword extraction docs? They can be found here.

Keyword Extraction API

Keywords are the important topics in your content and can be used to index data, generate tag clouds or for searching. AlchemyAPI's keyword extraction API is capable of finding keywords in text and ranking them. The sentiment can then be determined for each extracted keyword.

The keyword extraction API works on URLs, HTML documents and plain text. Just like every other feature, AlchemyAPI automatically detects the language of the content and then performs the appropriate analysis.

AlchemyAPI's keyword extraction algorithm employs sophisticated statistical algorithms and natural language processing technology to analyze your content and identify the relevant keywords. Keyword extraction is supported in over a half-dozen different languages, enabling even foreign-language content to be categorized and tagged.

Want to test out our keyword extraction API?

Keyword Extraction Example:

AlchemyAPI has raised $2 million to extend the capabilities of its deep learning technology that applies artificial intelligence to read and understand web pages, text documents, emails, tweets, and other forms of content. Access Venture Partners led the Series A round, which the company will use to ramp up its sales and marketing, make hires and launch new services.

excerpt from:

Keyword Relevance Sentiment
deep learning technology 0.973609 Positive
Access Venture Partners 0.943958 Neutral
artificial intelligence 0.762657 Positive
web pages 0.759048 Positive
text documents 0.757244 Positive
new services 0.717099 Positive
tweets 0.563718 Positive
hires 0.528816 Positive


Sentiment Analysis

As part of the keywords call, determine the negative or positive sentiment associated with each identified keyword.

Ranked Relevance

A relevance score is calculated for each keyword based on statistical analysis, and the results are returned sorted by relevancy.

Language Support

AlchemyAPI supports keyword extraction for content written in English, German, French, Italian, Portuguese, Russian, Spanish and Swedish.

Response Formats

Keyword extraction data can be returned in either JSON, XML, REL-TAG Microformats or RDF to fit the needs of your application.