Pass two text strings and receive the similarity percentage between them.
Plagiarism Detection: Educational institutions and content publishers can use the API to compare student submissions or published articles with existing documents. By detecting high similarity scores, it can identify potential cases of plagiarism or duplicate content.
Content Recommendation: E-commerce platforms, streaming services, and news websites can enhance user experience by recommending similar products, movies, or articles. The API can analyze user preferences and suggest items with high similarity scores to their previous selections.
Customer Service Chatbots: Customer support systems can use the API to improve chatbot responses. By analyzing the similarity between customer queries and a database of FAQs or past interactions, the chatbot can provide more accurate and relevant responses.
Document Clustering and Organization: Organizations dealing with large volumes of documents, such as legal firms or research institutions, can use the API to cluster and categorize documents based on their content similarity. This aids in efficient document management and retrieval.
Search Engine Enhancement: Search engines can leverage the API to improve search results. By comparing the similarity between user queries and indexed pages, the API can rank and display the most relevant results, enhancing the overall search experience for users.
Besides the number of API calls, there is no other limitation.
Returns a similarity score between 0 and 1 (1 is similar and 0 is dissimilar) of two given texts.
text_1 (required) - first input text. Maximum 5000 characters.
text_2 (required) - second input text. Maximum 5000 characters.
Check Similarity - Endpoint Features
| Object | Description |
|---|---|
Request Body |
[Required] Json |
Continue with Google
Continue with Github
{"similarity": 0.8126154541969299}
curl --location --request POST 'https://zylalabs.com/api/4392/text+similarity+analysis+api/5399/check+similarity' --header 'Authorization: Bearer YOUR_API_KEY'
--data-raw '{"text_1": "This is an example sentence.",
"text_2": "This is just another example 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 accepts plain text inputs in UTF-8 format. Both short phrases and long paragraphs can be processed, allowing for flexible use in various applications.
The API uses advanced NLP models to embed texts into 768-dimensional vectors and then computes the cosine similarity between these vectors to produce a similarity score ranging from -1 to 1, where 1 indicates identical texts.
The API utilizes state-of-the-art transformer-based models, such as BERT or its variants, for embedding texts. These models are pre-trained on large corpora and fine-tuned for high accuracy in capturing semantic meaning.
The API is optimized for low latency, typically responding within a few hundred milliseconds for standard requests. Performance may vary depending on the length and complexity of the input texts.
Yes, the API supports multiple languages, provided the underlying embedding model has been trained on multilingual data. This allows for accurate similarity calculations across different languages.
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