ameblo.over-update.download

Sign Up Sign In. A Base32-Crockford encoded API Key generator, validator, and converter to turn UUIDs into human readable API Keys. Node.js signature.

1. Api Key Generator Node Js Download
2. Key Generator For Games

Api Key Generator Node Js Download

This article shows you how to detect language, analyze sentiment, extract key phrases, and identify linked entities using the Text Analytics APIs with Node.JS.

Tip

For detailed API technical documentation and to see it in action, use the following links. You can also send POST requests from the built-in API test console. No setup is required, simply paste your resource key and JSON documents into the request:

• Latest stable API - v2.1
• Latest preview API - v3.0-Preview.1

Prerequisites

Injustice 2 legendary edition ps4. A key and endpoint for a Text Analytics resource. Azure Cognitive Services are represented by Azure resources that you subscribe to. Create a resource for Text Analytics using the Azure portal or Azure CLI on your local machine. You can also:

• Get a trial key valid for seven days for free. After signing up, it will be available on the Azure website.

• View your resource on the Azure portal

Detect language

The Language Detection API detects the language of a text document, using the Detect Language method.

1. Create a new Node.JS project in your favorite IDE or a folder on your desktop.
2. Add the code provided below to a new .js file.
3. Copy your key and endpoint into the code.
4. Run the program from your IDE or command line, for example npm start or node detect.js.

Language detection response

A successful response is returned in JSON, as shown in the following example:

Analyze sentiment

The Sentiment Analysis API detects the sentiment of a set of text records, using the Sentiment method. Sentiment analysis can be used to find out what customers think of your brand or topic by analyzing raw text for clues about positive or negative sentiment. The following example provides scores for two documents, one in English and another in Spanish.

1. Create a new Node.JS project in your favorite IDE or a folder on your desktop.
2. Add the code provided below to a new .js file.
3. Copy your Text Analytics key and endpoint into the code.
4. Run the program from your IDE or command line, for example npm start or node sentiment.js.

Key Generator For Games

Sentiment analysis response

The result is measured as positive if it's scored closer to 1.0 and negative if it's scored closer to 0.0.A successful response is returned in JSON, as shown in the following example:

Extract key phrases

The Key Phrase Extraction API extracts key-phrases from a text document, using the Key Phrases method. Key phrase extraction is used to quickly identify the main points of a document or text. The following example extracts key phrases for both English and Spanish documents.

1. Create a new Node.JS project in your favorite IDE or a folder on your desktop.
2. Add the code provided below to a new .js file.
3. Copy your Text Analytics key and endpoint into the code.
4. Run the program from your IDE or command line, for example npm start or node key-phrases.js.

Key phrase extraction response

A successful response is returned in JSON, as shown in the following example:

Identify linked entities

The Entities API identifies well-known entities in a text document, using the Entities method. Entities extract words from text, like 'United States', then give you the type and/or Wikipedia link for this word(s). The type for 'United States' is location, while the link to Wikipedia is https://en.wikipedia.org/wiki/United_States. The following example identifies entities for English documents.

1. Create a new Node.JS project in your favorite IDE or a folder on your desktop.
2. Add the code provided below to a new .js file.
3. Copy your Text analytics key and endpoint into the code
4. Run the program from your IDE or command line, for example npm start or node entities.js.

Entity extraction response

A successful response is returned in JSON, as shown in the following example:

Next steps

See also

Text Analytics overview
Frequently asked questions (FAQ)