Text Analysis API | Natural Language API

Text Analysis API

Natural Language Processing for Effective Understanding of Human-Generated Text

Extract meaning and insight from textual content with ease

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A Package of Information Retrieval, Machine Learning, and Natural Language APIs that Make it Easy to Analyze Text at Scale

We make it easy to parse, analyze, and extract structured data from human-generated text and content.

Content in; Data out

Process raw text or URLs
Clean, manageable JSON response

Real-time analysis

Analyze content in milliseconds
Ultra-low latency
Make up to 3 hits per second

NLP as a Service

State-of-the-art models
Production-ready performance
No NLP expertise required

Easily Accessible

RESTful API
SDKs for 7 languages
Plans starting from $49/month

Use the API for Free -- Forever

Sign up to get access to 1,000 hits per day for Free

Text Analytics Made Easy

Extract what matters from documents, web pages, blogs, Tweets, and reviews, or any textual content. Understand what or who a document mentions, what topics it deals with, and what the sentiment of a piece of text is.

Sentiment Analysis
Document-level Sentiment Analysis

Suitable for long or short-form text

Aspect-based Sentiment Analysis

Industry-specific models

Categorization
Classification

IAB-QAG & IPTC News Codes

Unsupervised Classification

Classify text on the fly

Extraction
Entity Extraction

Keywords, people, organizations, products, and more

Concept Extraction

Automatic topic discovery

Summarization

Automatically create summaries of text

Processing
Article Extraction

Remove clutter from web pages

Hashtags Suggestion

Generate optimal hashtags for social sharing

Related Phrases

Generate related words and phrases

Bring the Power of NLP to Whatever You’re Building

Process massive amounts of human-generated text as part of your app or solution

Social Listening & PR

Social media monitoring
Coverage analysis
Brand reputation

Business Process Improvement

Document processing
Process Automation
Business Intelligence and reporting

Editorial and Publishing Solutions

Content tagging
Article classification
Recommender systems

Ad-Tech Solutions

Semantic advertising
Domain classification

Built by Developers, for Developers

With our documentation and SDKs, you’ll be up and running with our API in minutes.

Visit our GitHub page to download our Node.js SDK repo, or you can run an example with the code below:

Installation:

$ npm install aylien_textapi
                        

You can then import and initiate the SDK easily:

var AYLIENTextAPI = require('aylien_textapi');
var textapi = new AYLIENTextAPI({
    application_id: "YourAppId",
    application_key: "YourAppKey"
});
textapi.sentiment({
    'text': 'John is a very good football player!'
}, function(error, response) {
    if (error === null) {
        console.log(response);
    }
});
                        

Visit our GitHub page to download our Python SDK repo, or you can run an example with the code below:

Installation:

$ pip install --upgrade aylien-apiclient
                        

You can then import and initiate the SDK easily:

from aylienapiclient import textapi
c = textapi.Client("YourAppID", "YourAppKey")
s = c.Sentiment({'text': 'John is a very good football player!'})
                        

Visit our GitHub page to download our PHP SDK repo, or you can run an example with the code below:

Installation:

Simply add the following to your composer.json:

{
    "require": {
        "aylien/textapi": "0.1.*"
    }
}
                        

You can then import and initiate the SDK easily:

$textapi = new AYLIEN\TextAPI("YourAppId", "YourAppKey");
$sentiment = $textapi->Sentiment(array(
    'text' => 'John is a very good football player!'
));
                        

Visit our GitHub page to download our Ruby SDK repo, or you can run an example with the code below:

Installation:

$ gem install aylien_text_api
                        

You can then import and initiate the SDK easily:

require 'aylien_text_api'

client = AylienTextApi::Client.new(app_id: "YourAppId",
app_key: "YourAppKey")

client.sentiment text: "John is a very good football player!"
                        

Visit our GitHub page to download our Java SDK repo, or you can run an example with the code below:

Installation:

Since the Text Analysis API is published to Maven Central, it is enough to add the dependency to the POM:

Using Maven:

<‌dependency>
<‌groupId>com.aylien.textapi<‌/groupId>
<‌artifactId>client<‌/artifactId>
<‌version>0.6.0<‌/version>
<‌/‌dependency>
                        

And for SBT users:

"com.aylien.textapi" % "client" % "0.1.0"
                        

Example:

import com.aylien.textapi.TextAPIClient;
import com.aylien.textapi.parameters.*;
import com.aylien.textapi.responses.*;
import java.net.URL;

class Example {
    public static void main(String[] args) throws Exception {
    TextAPIClient client = new TextAPIClient(
        "YourApplicationId", "YourApplicationKey");
    URL url = new URL(
        "http://www.bbc.com/news/science-environment-30097648");
    ConceptsParams.Builder builder = ConceptsParams.newBuilder();
    builder.setUrl(url);
    Concepts concepts = client.concepts(builder.build());
    System.out.println(concepts.getText());
    for (Concept c: concepts.getConcepts()) {
    System.out.print(c.getUri() + ": ");
    for (SurfaceForm sf: c.getSurfaceForms()) {
        System.out.print(sf.getString() + " ");
    }
    System.out.println();
    }

    LanguageParams languageParams = new LanguageParams(null, url);
    Language language = client.language(languageParams);
    System.out.printf("\nLanguage is: %s (%f)\n",
        language.getLanguage(), language.getConfidence());
    }
}
                        

Visit our GitHub page to download our Go SDK repo, or you can run an example with the code below:

Installation:

$ go get github.com/AYLIEN/aylien_textapi_go
                        

You can then import and initiate the SDK easily:

package main

import (
    "fmt"
    textapi "github.com/AYLIEN/aylien_textapi_go"
)

func main() {
    auth := textapi.Auth{"YourApplicationId", "YourApplicationKey"}
    client, err := textapi.NewClient(auth, true)
    if err != nil {
        panic(err)
    }
    text := "John is a very good football player!"
    sentimentParams := &textapi.SentimentParams{Text: text}
    sentiment, err := client.Sentiment(sentimentParams)
    if err != nil {
        panic(err)
    }
    fmt.Printf("%v\n", sentiment)
    languageParams := &textapi.LanguageParams{Text: text}
    language, err := client.Language(languageParams)
    if err != nil {
        panic(err)
    }
    fmt.Printf("%v\n", language)
}
                        

Visit our GitHub page to download our C# SDK repo, or you can run an example with the code below:

Installation:

The easiest way to get the C# SDK is to use NuGet.

PM> Install-Package Aylien.TextApi
                        

You can then import and initiate the SDK easily:

using Aylien.TextApi;
using System;

namespace ConsoleApplication
{
    class Program
    {
        static void Main(string[] args)
        {
            Client client = new Client(
                "YourApplicationID", "YourApplicationKey");
            Sentiment sentiment = client.Sentiment(
                text: "John is a very good football player!");
            Language language = client.Language(
                text: "John is a very good football player!");

            Console.WriteLine("Sentiment: {0} ({1})",
                sentiment.Polarity, sentiment.PolarityConfidence);
            Console.WriteLine("Language: {0} ({1})",
                language.Lang, language.Confidence);
        }
    }
}
                        
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