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Jaccard Similarity

ML Models & Algorithms
A distance-based algorithm measuring similarity based on overlapping n-grams or characters.

Jaccard Similarity is a Distance-based algorithm used for string matching. It computes the similarity between two strings using algorithms based on the presence of overlapping substrings (N-grams) in the dataset.
It is frequently used for detecting Duplicate Content and Hashtag Normalization. Although easy to calculate, Jaccard Similarity is noted as being slower than Levenshtein distance for large datasets and may be limited in flexibility when dealing with varying string lengths.

Related Concepts

Similarity Score TF-IDF with Cosine Similarity

Sources & References

Introduction to Machine Learning for SEOs Course
academy.mlforseo.com

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