Embark on a linguistic odyssey with our Text Similarity Checker API, a beacon of brilliance in the realm of natural language processing. Immerse your applications in the finesse of advanced machine learning as it deftly calculates the harmony between two textual pieces. This API transforms text into 768-dimensional vectors, a feat achieved by our groundbreaking Embeddings API, and then orchestrates a ballet of understanding through cosine similarity.
Picture a symphony where words waltz in the vastness of semantic space, harmonizing in a cosmic dance of similarity. Our state-of-the-art NLP models imbue your projects with unparalleled depth, capturing nuanced connections and resonances that escape ordinary methods. Seamlessly integrate this API to unlock a world where text transcends its literal boundaries, fostering a new era of contextual comprehension.
Whether you're revolutionizing search algorithms, refining recommendation systems, or ensuring plagiarism detection with finesse, the Text Similarity Checker API is your avant-garde ally. Join us in shaping a future where understanding is not just processed but celebrated—an intricately woven tapestry of linguistic brilliance illuminated by the guiding light of innovation.
Pass the two texts that you want to check its similarity.
Document Similarity Analysis:
Plagiarism Detection:
Search Engine Optimization (SEO):
Content Recommendations:
Legal Document Analysis:
Besides the number of API calls, there are no other limitations.
Returns a similarity score between 0 and 1 (1 is similar and 0 is dissimilar) of two given texts.
Get Similarity - Endpoint Features
Object | Description |
---|---|
Request Body |
[Required] Json |
{"similarity": 0.7571364641189575}
curl --location --request POST 'https://zylalabs.com/api/3010/text+similarity+checker+api/3175/get+similarity' --header 'Authorization: Bearer YOUR_API_KEY'
--data-raw '{ "text_1": "This is an example sentence.",
"text_2": "This is just another sample sentence." }'
Header | Description |
---|---|
Authorization
|
[Required] Should be Bearer access_key . See "Your API Access Key" above when you are subscribed. |
No long term commitments. One click upgrade/downgrade or cancellation. No questions asked.
The API leverages state-of-the-art NLP machine learning models to embed the input texts into 768-dimensional vectors using our Embeddings API. It then computes the cosine similarity between these vectors to determine their similarity score.
While the API is designed to excel in English, its capabilities can extend to other languages. However, optimal performance is achieved for English, and users exploring other languages should consider language-specific APIs for precision.
The API does have input size limitations. For extensive texts, consider preprocessing or breaking down the content into smaller, meaningful segments to ensure efficient and accurate similarity computations.
Absolutely. The API is designed to provide real-time similarity scores. Its efficiency makes it suitable for applications demanding instantaneous responses, such as chatbots, content recommendation systems, and live data analysis.
The API considers context through its embedding process, capturing semantic nuances. While it excels in handling polysemy, users should be aware that context plays a crucial role, and results may vary based on the complexity of the language.
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