docspell/website/site/static/js/searchhelper.js

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JavaScript
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2020-09-29 22:17:18 +00:00
// Taken from mdbook
// The strategy is as follows:
// First, assign a value to each word in the document:
// Words that correspond to search terms (stemmer aware): 40
// Normal words: 2
// First word in a sentence: 8
// Then use a sliding window with a constant number of words and count the
// sum of the values of the words within the window. Then use the window that got the
// maximum sum. If there are multiple maximas, then get the last one.
// Enclose the terms in *.
function makeTeaser(body, terms) {
var TERM_WEIGHT = 40;
var NORMAL_WORD_WEIGHT = 2;
var FIRST_WORD_WEIGHT = 8;
var TEASER_MAX_WORDS = 30;
var stemmedTerms = terms.map(function (w) {
return elasticlunr.stemmer(w.toLowerCase());
});
var termFound = false;
var index = 0;
var weighted = []; // contains elements of ["word", weight, index_in_document]
// split in sentences, then words
var sentences = body.toLowerCase().split(". ");
for (var i in sentences) {
var words = sentences[i].split(" ");
var value = FIRST_WORD_WEIGHT;
for (var j in words) {
var word = words[j];
if (word.length > 0) {
for (var k in stemmedTerms) {
if (elasticlunr.stemmer(word).startsWith(stemmedTerms[k])) {
value = TERM_WEIGHT;
termFound = true;
}
}
weighted.push([word, value, index]);
value = NORMAL_WORD_WEIGHT;
}
index += word.length;
index += 1; // ' ' or '.' if last word in sentence
}
index += 1; // because we split at a two-char boundary '. '
}
if (weighted.length === 0) {
return body;
}
var windowWeights = [];
var windowSize = Math.min(weighted.length, TEASER_MAX_WORDS);
// We add a window with all the weights first
var curSum = 0;
for (var i = 0; i < windowSize; i++) {
curSum += weighted[i][1];
}
windowWeights.push(curSum);
for (var i = 0; i < weighted.length - windowSize; i++) {
curSum -= weighted[i][1];
curSum += weighted[i + windowSize][1];
windowWeights.push(curSum);
}
// If we didn't find the term, just pick the first window
var maxSumIndex = 0;
if (termFound) {
var maxFound = 0;
// backwards
for (var i = windowWeights.length - 1; i >= 0; i--) {
if (windowWeights[i] > maxFound) {
maxFound = windowWeights[i];
maxSumIndex = i;
}
}
}
var teaser = [];
var startIndex = weighted[maxSumIndex][2];
for (var i = maxSumIndex; i < maxSumIndex + windowSize; i++) {
var word = weighted[i];
if (startIndex < word[2]) {
// missing text from index to start of `word`
teaser.push(body.substring(startIndex, word[2]));
startIndex = word[2];
}
// add <em/> around search terms
if (word[1] === TERM_WEIGHT) {
teaser.push("**");
}
startIndex = word[2] + word[0].length;
teaser.push(body.substring(word[2], startIndex));
if (word[1] === TERM_WEIGHT) {
teaser.push("**");
}
}
teaser.push("…");
return teaser.join("");
}
var index = elasticlunr.Index.load(window.searchIndex);
var initElmSearch = function(elmSearch) {
var options = {
bool: "AND",
fields: {
title: {boost: 2},
body: {boost: 1},
}
};
elmSearch.ports.doSearch.subscribe(function(str) {
var results = index.search(str, options);
for (var i = 0; i < results.length; i ++) {
var teaser = makeTeaser(results[i].doc.body, str.split(" "));
results[i].doc.body = teaser;
}
elmSearch.ports.receiveSearch.send(results);
});
};