Nice! It wouldn't be much work to add fuzzy-search functionality (all results with a prefix edit-distance below some threshold delta, so that a search for "hack

Nice! It wouldn't be much work to add fuzzy-search functionality (all results with a prefix edit-distance below some threshold delta, so that a search for "hackrnew" matches "hackernews"). Basically, what you would do is you add an additional inverted index, but this time the keys are n-grams of words in your document collection (typically 3-grams), and the postings are the words (or their ID) in which these n-grams occur. There is then a nice lemma that basically says the following (where PED is the prefix edit distance, and N(x) are the n-grams of word x): If PED(x, y) <= delta, then |N(x) ∩ N(y)| >= |N(x)| - n ∙ delta That is, x and y must have at least |N(x)| - n ∙ delta n-grams in common to have a PED(x, y) less then or equal to delta. If you now have an input x, you calculate N(x) and retrieve all postings from the n-gram index for each n-gram of x. You can now merge all of these postings and get a list that looks like this: [worda, worda, worda, wordb, wordb, wordc] (for each q-gram x and some word y have in common, you get one entry of y). If you merge the duplicates, you get: [(worda, 3), (wordb, 2), (wordc, 1)], and for each y (in this case, worda, wordb, wordc), the number in the corresponding tuple is |N(x) ∩ N(y)|. If this number is larger than |N(x)| - n ∙ delta, you explicitly compute PED(x, y) and check whether it is below your threshold. If the number is smaller, you can simply skip it, saving you large amounts of costly PED calculations. Your result is a list of words y with a PED(x, y) to the input x below some threshold, and you can then use this list of words to query your existing index. I used this approach many years ago to implement a fuzzy client-side JS search engine on https://dont.watch/ https://dont.watch/ (if you look into the JS code, you can see that the inverted index and the (compressed) n-gram index are simply transferred in the JS-file). The actual search engine is around 300 lines of JS, with no external dependencies and some very basic heuristics to improve the search results).