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Add similarity search based on Levenshtein distance to the highlight feature of SearchJumper.
// ==UserScript==
// @name SearchJumper levenshtein addon
// @name:zh-CN 搜索酱单词模式扩展
// @name:zh-TW 搜尋醬單詞模式擴展
// @namespace hoothin
// @version 0.2
// @description Add similarity search based on Levenshtein distance to the highlight feature of SearchJumper.
// @description:zh-CN 为搜索酱的页内高亮添加基于莱文斯坦距离的相似度查找
// @description:zh-TW 為搜尋醬的頁内高亮添加基於萊文斯坦距離的相似度查找
// @author hoothin
// @match *://*/*
// @grant unsafeWindow
// @run-at document-start
// ==/UserScript==
(function() {
'use strict';
var _unsafeWindow = (typeof unsafeWindow == 'undefined') ? window : unsafeWindow;
if (!_unsafeWindow.searchJumperAddons) _unsafeWindow.searchJumperAddons = [];
function levenshteinDistance(a, b) {
//構造矩陣
const distanceMatrix = Array(b.length + 1).fill(null).map(() => Array(a.length + 1).fill(null));
//第一行
for (let i = 0; i <= a.length; i += 1) {
distanceMatrix[0][i] = i;
}
//第一列
for (let j = 0; j <= b.length; j += 1) {
distanceMatrix[j][0] = j;
}
for (let j = 1; j <= b.length; j += 1) {
for (let i = 1; i <= a.length; i += 1) {
const indicator = a[i - 1] === b[j - 1] ? 0 : 1;
distanceMatrix[j][i] = Math.min(
distanceMatrix[j][i - 1] + 1, // 前一個，增加位數，必須加一
distanceMatrix[j - 1][i] + 1, // 上一個，增加位數，必須加一
distanceMatrix[j - 1][i - 1] + indicator, // 斜方向一個，位數不變
);
}
}
return distanceMatrix[b.length][a.length];
}
const gapStr = "[\n\/\\'\"‘’“”,.!\?，。！？…\(\) ]";
const gapStrs = new RegExp(gapStr + "+", "g");
_unsafeWindow.searchJumperAddons.push({
name: "Levenshtein",
type: "findInPage",
sort: 0,
run: (text, keywords) => {
if (!text || !keywords) return {matched: false};
if (keywords.charCodeAt(0) > 255) {
let len = keywords.length;
let pos = text.toUpperCase().indexOf(keywords.toUpperCase());
return {matched: pos != -1, pos: pos, len: len};
}
text = text.toLowerCase();
keywords = keywords.toLowerCase();
let wordArr = text.replace(gapStrs, " ").split(" ");
let kwArr = keywords.replace(gapStrs, " ").split(" ");
let matched = false, pos = -1, len = 0, matchedStr = [];
for (let i = 0; i < wordArr.length; i++) {
matched = true;
matchedStr = [];
for (let j = 0; j < kwArr.length; j++) {
let kwLen = kwArr[j].length;
let maxTolerance = kwLen>>2;
if (kwLen > 3) maxTolerance++;
if (!wordArr[i + j] || levenshteinDistance(kwArr[j], wordArr[i + j]) > maxTolerance) {
matched = false;
break;
} else {
matchedStr.push(wordArr[i + j].replace(/([\[\]\(\)\^\$\.\+\*\?\|\{\}\-])/g, "\\$1"));
}
}
if (matched) {
break;
}
}
if (matched) {
let wordMatch = text.match(new RegExp(`(\\b|\\s)(` + matchedStr.join(gapStr + "+") + `)(\\b|\\s)`, "i"));
if (wordMatch) {
let content = wordMatch[2];
len = content.length;
pos = wordMatch.index + wordMatch[1].length;
}
}
return {matched: matched, pos: pos, len: len};
}
});
})();