keyword generator

Keyword Extractor is a powerful tool in text analysis that can be used to index data, generate tag clouds and accelerate the searching time. It generates an extensive list of relevant keywords and phrases to make research more context focussed.

demo
Keyword
Phrases
keywords

Ready to Integrate? Check out the API wrappers below

For setup and installation instruction, please visit our Github Page
import paralleldots.ParallelDots;
// Get your API key here
ParallelDots pd = new ParallelDots("<YOUR_API_KEY>");
import paralleldots.ParallelDots;
ParallelDots pd = new ParallelDots();
String keywords = pd.keywords("Prime Minister Narendra Modi tweeted a link to the speech Human Resource Development Minister Smriti Irani made in the Lok Sabha during the debate on the ongoing JNU row and the suicide of Dalit scholar Rohith Vemula at the Hyderabad Central University.");
System.out.println(keywords);
//Response
{
	"keywords": [
		{
			"relevance_score": 6,
			"keyword": "Human Resource Development Minister Smriti Irani"
		}, 
		{
			"relevance_score": 4,
			"keyword": "Prime Minister Narendra Modi"
		}, 
		{
			"relevance_score": 3,
			"keyword": "Hyderabad Central University"
		}, 
		{
			"relevance_score": 3,
			"keyword": "ongoing JNU row"
		}, 
		{
			"relevance_score": 2,
			"keyword": "Dalit scholar"
		}, 
		{
			"relevance_score": 2,
			"keyword": "Lok Sabha"
		}, 
		{
			"relevance_score": 2,
			"keyword": "Rohith Vemula"
		}
	]
}
For setup and installation instruction, please visit our Github Page
from paralleldots import set_api_key, get_api_key
# Get your API key here
set_api_key(<YOUR_API_KEY>)
get_api_key()
from paralleldots import similarity, ner, taxonomy, sentiment, keywords, intent, emotion, multilang, abuse
String keywords = pd.keywords("Prime Minister Narendra Modi tweeted a link to the speech Human Resource Development Minister Smriti Irani made in the Lok Sabha during the debate on the ongoing JNU row and the suicide of Dalit scholar Rohith Vemula at the Hyderabad Central University.");
#Response
{
	"keywords": [
		{
			"relevance_score": 6,
			"keyword": "Human Resource Development Minister Smriti Irani"
		}, 
		{
			"relevance_score": 4,
			"keyword": "Prime Minister Narendra Modi"
		}, 
		{
			"relevance_score": 3,
			"keyword": "Hyderabad Central University"
		}, 
		{
			"relevance_score": 3,
			"keyword": "ongoing JNU row"
		}, 
		{
			"relevance_score": 2,
			"keyword": "Dalit scholar"
		}, 
		{
			"relevance_score": 2,
			"keyword": "Lok Sabha"
		}, 
		{
			"relevance_score": 2,
			"keyword": "Rohith Vemula"
		}
	]
}
For setup and installation instruction, please visit our Github Page
require 'paralleldots'
# Get your API key here
set_api_key(<YOUR_API_KEY>)
get_api_key()
require 'paralleldots'
String keywords = pd.keywords("Prime Minister Narendra Modi tweeted a link to the speech Human Resource Development Minister Smriti Irani made in the Lok Sabha during the debate on the ongoing JNU row and the suicide of Dalit scholar Rohith Vemula at the Hyderabad Central University.");
#Response
{
	"keywords": [
		{
			"relevance_score": 6,
			"keyword": "Human Resource Development Minister Smriti Irani"
		}, 
		{
			"relevance_score": 4,
			"keyword": "Prime Minister Narendra Modi"
		}, 
		{
			"relevance_score": 3,
			"keyword": "Hyderabad Central University"
		}, 
		{
			"relevance_score": 3,
			"keyword": "ongoing JNU row"
		}, 
		{
			"relevance_score": 2,
			"keyword": "Dalit scholar"
		}, 
		{
			"relevance_score": 2,
			"keyword": "Lok Sabha"
		}, 
		{
			"relevance_score": 2,
			"keyword": "Rohith Vemula"
		}
	]
}
For setup and installation instruction, please visit our Github Page
using ParallelDots
# Get your API key here
ParallelDots.api pd = new ParallelDots.api("<YOUR_API_KEY>");
String keywords = pd.keywords("Prime Minister Narendra Modi tweeted a link to the speech Human Resource Development Minister Smriti Irani made in the Lok Sabha during the debate on the ongoing JNU row and the suicide of Dalit scholar Rohith Vemula at the Hyderabad Central University.");
Console.WriteLine(keywords);
#Response
{
	"keywords": [
		{
			"relevance_score": 6,
			"keyword": "Human Resource Development Minister Smriti Irani"
		}, 
		{
			"relevance_score": 4,
			"keyword": "Prime Minister Narendra Modi"
		}, 
		{
			"relevance_score": 3,
			"keyword": "Hyderabad Central University"
		}, 
		{
			"relevance_score": 3,
			"keyword": "ongoing JNU row"
		}, 
		{
			"relevance_score": 2,
			"keyword": "Dalit scholar"
		}, 
		{
			"relevance_score": 2,
			"keyword": "Lok Sabha"
		}, 
		{
			"relevance_score": 2,
			"keyword": "Rohith Vemula"
		}
	]
}
For setup and installation instruction, please visit our Github Page
require(__DIR__ . '/vendor/paralleldots/apis/autoload.php');
# Get your API key here
set_api_key("<YOUR_API_KEY>");
get_api_key();
require(__DIR__ . '/vendor/paralleldots/apis/autoload.php');
String keywords = pd.keywords("Prime Minister Narendra Modi tweeted a link to the speech Human Resource Development Minister Smriti Irani made in the Lok Sabha during the debate on the ongoing JNU row and the suicide of Dalit scholar Rohith Vemula at the Hyderabad Central University.");
#Response
{
	"keywords": [
		{
			"relevance_score": 6,
			"keyword": "Human Resource Development Minister Smriti Irani"
		}, 
		{
			"relevance_score": 4,
			"keyword": "Prime Minister Narendra Modi"
		}, 
		{
			"relevance_score": 3,
			"keyword": "Hyderabad Central University"
		}, 
		{
			"relevance_score": 3,
			"keyword": "ongoing JNU row"
		}, 
		{
			"relevance_score": 2,
			"keyword": "Dalit scholar"
		}, 
		{
			"relevance_score": 2,
			"keyword": "Lok Sabha"
		}, 
		{
			"relevance_score": 2,
			"keyword": "Rohith Vemula"
		}
	]
}

#keyword generator

function name
paralleldots_keywords
description

Keyword Generator API is a powerful tool in text analysis that is used to index data, generate tag clouds and accelerate the searching time. Using the function paralleldots_keywords you can generate an extensive list of relevant keywords and phrases to make research more context based.
Consider the following example where keywords are generated in the following sentence “For the Yankees, it took a stunning comeback after being down 2-0 to the Indians in the American League Division Series.”

example

Using the function paralleldots_sentiment you can analyse any textual content and in return get the sentiment attached to the text.

how our keyword generator api works?

Keywords Generator API helps finding and suggesting most important keywords in a text and ranking them. A relevance score is calculated for each keyword based on statistical analysis, and the results are returned sorted by relevancy.

It uses the famous syntaxnet algorithm by Google and statistical analysis of text to retrieve important keywords from textual data.

Our Keyword Generator successfully generates an extensive list of most relevant keywords and keyword phrases. It also makes keyword research process for Search engine optimization more context focussed.

keyword generator use cases

Keyword Generator is a powerful tool in text analysis that can be used to index data, generate tag clouds and accelerate the searching time. Generating keywords from text can help you in marketing and competitive research. You can extract popular topics from online conversation about your brand and competitor. When you deal with a large corpus, keyword generator can help you reduce efforts and increase efficiency of analyzing and categorizing the data.

why our keyword generator api ?
Accurate

Highly accurate classification of unstructured textual data.

Real Time

State of the art technology to provide accurate results real-time.

Customizable

Can be trained on custom dataset to obtain similar accuracy and performance.