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@leolee9086/string-metrics-dice

v1.0.1

Published

Sørensen-Dice 系数算法库

Readme

String Metrics Dice

高性能 Sørensen-Dice 系数算法库,支持多种实现变体和竞争系统。

📦 安装

npm install string-metrics-dice

🚀 快速开始

基础使用

import { computeDiceCoefficient } from 'string-metrics-dice';

// 计算两个字符串的 Dice 系数
const similarity = computeDiceCoefficient('hello', 'helo');
console.log(similarity); // 0.8571428571428571

// 使用选项
const similarity2 = computeDiceCoefficient('Hello', 'helo', {
  normalize: true
});
console.log(similarity2); // 0.8571428571428571

WASM 高性能版本

import { computeDiceCoefficientWasm } from 'string-metrics-dice/wasm';

// 异步初始化
await computeDiceCoefficientWasm.init();

// 高性能计算
const similarity = computeDiceCoefficientWasm.compute('hello', 'helo');
console.log(similarity); // 0.8571428571428571

📚 API 文档

computeDiceCoefficient(str1, str2, options?)

计算两个字符串的 Sørensen-Dice 系数。

参数:

  • str1 (string): 第一个字符串
  • str2 (string): 第二个字符串
  • options (object, 可选): 计算选项
    • normalize (boolean): 是否进行 Unicode 标准化,默认 false
    • nGramSize (number): n-gram 大小,默认 2 (bigram)

返回值:

  • number: Dice 系数,范围 [0, 1],1 表示完全相同

computeDiceDistance(str1, str2, options?)

计算两个字符串的 Dice 距离(1 - Dice 系数)。

参数:computeDiceCoefficient

返回值:

  • number: Dice 距离,范围 [0, 1],0 表示完全相同

🏗️ 算法原理

Sørensen-Dice 系数基于字符 n-gram 的重叠度计算:

Dice = 2 * |A ∩ B| / (|A| + |B|)

其中:

  • A, B 是两个字符串的 n-gram 集合
  • |A ∩ B| 是交集大小
  • |A|, |B| 是各自集合大小

🔧 开发

安装依赖

npm install

运行测试

npm test

运行基准测试

npm run bench

构建 WASM

npm run build:wasm

许可证

AGPL=3.0 License