String Comparisons

This library offers a range of functions to calculate text similarity, allowing you to measure the likeness of text data in an application. It implements well-established similarity metrics. The library currently supports the following algorithms:

• Cosine Similarity
• Jaccard Similarity
• Jaro Similarity
• Damerau-Levenshtein Distance
• Hamming Distance
• Levenshtein Distance
• Smith-Waterman Alignment
• Sørensen-Dice Coefficient
• Jaccard Similarity based on Trigrams
• Szymkiewicz Simpson Overlap
• N-Gram
• Q-Gram
• Optimal String Alignment

Installation

Assuming you have Node.js and npm/yarn/pnpm installed, install the library using:

# Install the 'string-comparisons' package using npm
npm install string-comparisons

# Alternatively, install the 'string-comparisons' package using yarn
yarn add string-comparisons

# Or, install the 'string-comparisons' package using pnpm
pnpm add string-comparisons

Docs

Find more information on the algorithms by accessing the class documentation of each implemented algorithm.

String Similarity Algorithm Comparison

| Algorithm | Normalized | Metric | Similarity | Distance | Space Complexity | |------------------------|------------|-----------------------------------------|------------|----------|------------------| | cosine.js | Yes | Vector Space Model | ✓ | | O(n) | | jaro.js | No | Edit Distance | ✓ | | O(min(n, m)) | | jaccard.js | No | Set Theory | ✓ | | O(min(n, m)) | | damerauLevenshtein.js | No | Edit Distance | | ✓ | O(max(n, m)²) | | hammingDistance.js | No | Bitwise Operations | ✓ | | O(1) | | jaroWinkler.js | No | Edit Distance | ✓ | | O(min(n, m)) | | levenshtein.js | No | Edit Distance | | ✓ | O(max(n, m)²) | | smithWaterman.js | No | Dynamic Programming (Local Alignment) | ✓ | | O(n * m) | | sorensenDice.js | No | Set Theory | ✓ | | O(min(n, m)) | | trigram.js | No | N-gram Overlap | ✓ | | O(n²) | | szymkiewiczSimpsonOverlap.js | Yes | Overlap Coefficient | ✓ | | O(min(m, n)) | | nGram.js | Yes | Jaccard similarity coefficient | ✓ | | O(m * n) | | qGram.js | Yes | Jaccard similarity coefficient | ✓ | | O(n + m) | | optimalStringAlignment.js | No | Edit distance | | ✓ | O(max(n, m)²) |

Explanation of Columns:

• Normalized: Indicates whether the algorithm produces a score between 0 and 1 (normalized).
• Metric: The underlying mathematical concept used for comparison.
• Similarity: Whether the algorithm outputs a higher score for more similar strings.
• Distance: Whether the algorithm outputs a lower score for more similar strings. (One algorithm might use similarity, another distance - they provide the opposite information).
• Space Complexity: The amount of extra memory the algorithm needs to run the comparison.

Notes:

• ✓ indicates the algorithm applies to that category.
• Some algorithms can be used for both similarity and distance calculations depending on the interpretation of the score.

Example Usage

import StringComparisons from 'string-comparisons';

const { Cosine, Jaccard, Jaro, DamerauLevenshtein, HammingDistance, JaroWrinker, Levenshtein, SmithWaterman, SorensenDice, Trigram } = StringComparisons;

const string1 = 'programming';
const string2 = 'programmer';


console.log('Jaro-Winkler similarity:', JaroWrinker.similarity(string1, string2)); // Output: ~0.9054545454545454
console.log('Levenshtein distance:', Levenshtein.similarity(string1, string2)); // Output: 3
console.log('Smith-Waterman similarity:', SmithWaterman.similarity(string1, string2)); // Output: 16

const set1 = new Set([1, 2, 3]);
const set2 = new Set([2, 3, 4]);

console.log('Sørensen-Dice similarity:', SorensenDice.similarity(set1, set2)); // Output: 0.6666666666666667

const trigram1 = 'hello';
const trigram2 = 'world';

console.log('Trigram Jaccard similarity:', Trigram.similarity(trigram1, trigram2)); // Output: 0 (no shared trigrams)

// so on

Contributing

We encourage contributions to this library! Feel free to fork the repository, make your changes, and submit pull requests.

Support the Project ⭐

If you feel awesome and want to support us in a small way, please consider starring and sharing the repo! This helps us get visibility and allow the community to grow. 🙏

Contact Us

If you have any questions or feedback, please don't hesitate to contact us at [email protected], or reach out to Suman directly. We hope you find this resource helpful 💜.

License Information

This project is licensed under the MIT , which means that you are free to use, modify, and distribute the code as long as you comply with the terms of the license.

Resources

• String Similarity Comparison in JS with Examples
• Cosine similarity between two sentences
• The complete guide to string similarity algorithms
• N-Gram Similarity and Distance
• Approximate string-matching with q-grams and maximal matches
• Research on string similarity algorithm based on Levenshtein Distance
• String similarity search and join: a survey