FuzzyJS

A lightweight fuzzy search implementation for JavaScript. It uses the Overlap coefficient for an intersection test, the Damerau–Levenshtein algorithm to measure the edit distance between token pairs, and an n-gram hashtable to probabilistically determine the total weighted similarity score.

Dependencies

None. Pure JavaScript.

Basic Usage

1. Create a new Fuzzy() object.

var fuzzy = new Fuzzy();

2. Set the parameters for the search. The scores calculated by the engine range from 0 (completely different) to 1.0 (exact match).

fuzzy.options = {
    sort : true,            // Sort results by final score
    n_size : 3,             // N-gram size
    min_query : 2,          // Minimum query length
    score_threshold : 0.4,  // Minimum total similarity score
    edit_threshold : 0.6,   // Minimum edit score
    all_matches : true      // Return all potential matches?
};

3. Index the search space into the Fuzzy engine.

var keys = ["Hello", "Helper", "world", "bob"];
fuzzy.index(keys);

4. Search for a query and get an array of matches.

var results = fuzzy.search("hell"); // ["Hello", "Helper"]