Semantic Analysis

Analyze how close different text contents are with respect to each other

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Relatedness

4.93

Semantic Analysis

Semantic Analysis API helps users cluster similar articles by understanding the relatedness between different content and streamlines research by eliminating redundant text contents.API can help bloggers, publishing and media houses to write more engaging stories by retrieving similar articles from past quickly, and news aggregators to combine similar news from different sources to reduce clutter in the feeds of their readers.

How our Semantic Analysis API works?

Semantic similarity API understands relatedness between different pieces of text. It helps in comparing the structure and meaning of the text which can be used to extract similar text and phrases from corpus.


Our API converts textual information to its corresponding document embeddings and the cosine similarity between the two embeddings is scaled to provide the result. The document embeddings are made using Recursive Auto Encoders. These encoders try to reconstruct the given sentences to determine their respective document embeddings.Semantic Similarity API provides a score on a range of 0-5 (0-Not similar, 5-Almost same)

Semantic Analysis Use cases

Documents

Production of New Content

Semantic analysis provides contextual information about the content to create more engagement in lesser time and cost.

Feed Clustering

News and content aggregators can use the API to combine similar content from different sources to automatically curate the feed for their readers.

News feed
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Customer Feedback

Analyze similar type of problems faced by consumers of your brand, product and use insights to take better business decision. Lesser Response time can lead to better user experience

Semantic Search

Semantic Similarity API can help in creating a more contextual search engine for your content that goes beyond matching keywords and sorting by frequencies. For eg: using our API, searching for Ronaldo will also present results on Messi (or Real Madrid)

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Why Our Semantic Similarity API

Best Solution

One of the very few Semantic Similarity APIs available to provide highly accurate results in real-time

Custom Dataset

Can be trained on custom datasets like legal documents without any manual annotations required

Frequently Updated

Our Models are updated fortnightly on news and social media content to ensure contextuality on new topics as they emerge

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