This API uses algorithms that can be used for string similarity comparison such as Levenshtein, Jaro-Winkler and Dice. These algorithms compare the characters or words in two strings and assign a score based on their similarity. For example, the Levenshtein distance algorithm calculates the minimum number of insertions, deletions or substitutions needed to transform one string into another. The Jaro-Winkler distance algorithm calculates a similarity score based on the number of matching characters and the number of transpositions required to transform one string into another.
A Text Similarity API can be used for a variety of purposes, such as data deduplication, record linking and fuzzy matching. For example, in data deduplication, an API can be used to compare two records in a database to determine whether they represent the same entity, such as a customer or a product. In record linking, an API can be used to link records from different data sources that represent the same entity. In fuzzy matching, an API can be used to match text strings that may contain misspellings, typos, or formatting variations.
One of the main advantages of using a Text Similarity API is that it provides high accuracy for string matching. In addition, APIs can be used to compare words quickly and efficiently, making it easier to process data or data streams in real time.The API offers powerful functionality with precision. This makes it easy for your users to find exact measurements and discover the percentage of similar text found in your strings. This allows you to tailor the search results to your specific needs, making this API a flexible and versatile tool for your applications or string-related services.
In summary, the Text Similarity API is a useful tool for comparing text strings and determining their similarity. By using an API, developers can create applications that rely on string similarity comparison, such as data deduplication, logging, and so on.
It will receive parameters and provide you with a JSON.
Data Deduplication: Can be used to identify duplicate records in a database, such as duplicate customer entries or duplicate product listings.
Fuzzy matching: Can be used to match similar text strings, such as names or addresses, even if they contain misspellings or variations.
Record linking: This API can be used to differentiate records from different data sources that represent a similar entity, such as a customer or patient.
Search engine optimization: This can be used to identify duplicate content on a Web site, which can negatively affect search engine rankings.
Fraud detection: Can be used to identify fraudulent activity, such as detecting similar user accounts or transaction patterns.
1 request per second in the free plan.
To use this endpoint all you have to do is insert 2 strings in the parameters.
Object | Description |
---|---|
string1 |
[Required] |
string2 |
[Required] |
{"string1":"twitter","string2":"twitte","results":{"jaro-wrinkler":0.9714285714285714,"levenshtein-inverse":1,"dice":0.9090909090909091}}
curl --location --request GET 'https://zylalabs.com/api/1961/text+similarity+api/1711/get+text+comparison?string1=twitter&string2=twitte' --header 'Authorization: Bearer YOUR_API_KEY'
To use this endpoint all you have to do is insert 2 strings in the parameters.
Object | Description |
---|---|
Request Body |
[Required] Json |
{"string1":"twitter","string2":"twitte","results":{"jaro-wrinkler":0.9714285714285714,"levenshtein-inverse":1,"dice":0.9090909090909091}}
curl --location --request POST 'https://zylalabs.com/api/1961/text+similarity+api/1712/get+comparison' --header 'Authorization: Bearer YOUR_API_KEY'
After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the Text Similarity API REST API, simply include your bearer token in the Authorization header.
Header | Description |
---|---|
Authorization
|
[Required] Should be Bearer access_key . See "Your API Access Key" above when you are subscribed. |
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Service Level:
100%
Response Time:
1,289ms