Text Analytics API
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Use Cases for Text Analytics APIs
Perform sentiments analysis on news articles collected by News API or from other text documents using our sentiments analysis API.
Filter news articles by using language detection APIs
Extract company names, geographical locations etc. from text documents using named entity extraction (NER) API.
Summarize large text documents such as job descriptions, news articles, PR documents using our text summarization APIs.
Extract keywords from text using our keywords extraction APIs.
Specrom Text Analytics API Pricing
APIs are available for all the typical text analytics tasks such as language detection, keywords generation, name entity recognition (NER), text summarization, semantic similarity between two documents, and sentence and document level sentiments analysis.
We also have some pretrained classifiers to predict labels for abusive content, gender etc.
We work closely with our clients to train classifiers and NER for their own domain need and we do labeling of data ourselves for maximum accuracy.
Please Contact us now to get free access to our API keys.
Pricing
| Basic | Pro | Ultra | Custom | |
|---|---|---|---|---|
| Units* | 5000/month | 100,000/month | 300,000/month | 0 - unlimited |
| Monthly Cost | Free | $49/month | $99/month | Ask for a quote |
| Language detection | Y | Y | Y | |
| Keywords generation | Y | Y | Y | |
| Text summarization | Y | Y | Y | |
| Sentiment analysis models | 1 | 2 | 4 | |
| Semantic similarity | N | Y | Y | |
| Topic Modeling | N | Y | Y | |
| Name Entity recognition (NERs) | N | Y | Y | |
| No. of Pretrained classifiers | N | 4 | 4 | |
| Custom Classifiers | N | N | 4 | |
| Custom NERs | N | N | 2 |
*1 unit equals 1 cpu second
**Free tier available for plans directly with as well as through our Algorithmia marketplace page
API Demo Pages
Extract keywords from text: Extraction from Sentence
Generate suggestive keywords from a seed keyword: This algorithm generates suggestive keywords similar to what Google Ads considers to be “closely related”.
Get Sentiments Score from Text: Gives positive, negative and neutral sentiments from text.
Natural Language Identification: Guess the language of a input text for 97 pretrained natural languages.
Text Summarization: Text Summarizer using latest BERT model
Name Entity Recognition: Extract named entities from text using latest BERT models
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