Q-gram (n-gram) similarity algorithm
Online tool to test the Q-gram (n-gram) similarity algorithm
What is the Q-gram (n-gram) similarity algorithm?
The Q-gram (n-gram) similarity algorithm is a string-matching algorithm that is used to compare two strings and determine their similarity. It does this by dividing each string into substrings of length Q (where Q is a positive integer), and then comparing the substrings to determine how many of them are the same in both strings. The result is a measure of the similarity of the two strings, with a higher value indicating a greater degree of similarity. The Q-gram algorithm is often used in natural language processing and other fields where the comparison of strings is important. It is a fast and efficient algorithm that can be used to quickly compare large amounts of text data.
At Tilores we use the Q-gram (also known as n-gram) algorithm as one of the potential data record matching algorithms for entity resolution. These can be combined with other matching algorithms to allow fine-tuned data matching and deduplication.
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About Tilores
When you need to do fuzzy matching on high-volume data in real-time, you need a built-for-purpose technology: enter Tilores.
Consistently fast search response times
Built for unlimited serverless scaling
Real-time data ingestion and simultaneous search.
Configure matching rules easily in the UI
Data privacy compliant by design