diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..ea8c4bf --- /dev/null +++ b/.gitignore @@ -0,0 +1 @@ +/target diff --git a/Cargo.lock b/Cargo.lock new file mode 100644 index 0000000..71cc2db --- /dev/null +++ b/Cargo.lock @@ -0,0 +1,16 @@ +# This file is automatically @generated by Cargo. +# It is not intended for manual editing. +version = 4 + +[[package]] +name = "levenshtein" +version = "1.0.5" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "db13adb97ab515a3691f56e4dbab09283d0b86cb45abd991d8634a9d6f501760" + +[[package]] +name = "word_correction" +version = "0.1.0" +dependencies = [ + "levenshtein", +] diff --git a/Cargo.toml b/Cargo.toml new file mode 100644 index 0000000..85f4806 --- /dev/null +++ b/Cargo.toml @@ -0,0 +1,7 @@ +[package] +name = "word_correction" +version = "0.1.0" +edition = "2024" + +[dependencies] +levenshtein = "1.0.5" \ No newline at end of file diff --git a/README.md b/README.md index e69de29..3671e0c 100644 --- a/README.md +++ b/README.md @@ -0,0 +1,18 @@ +# Word Correction +## YinMo19 + +A simple word correction program written in rust, while it is from a c course extra homework problem. +It uses an algorithm to find the most similar word to the input word, which called Levenshtein distance. +The parse of the input file is the most thing in the program do. +The two big acceptance of the program is the levenshtein distance algorithm realization and the sort/binary_search of the word in dict. + +You can just run +```bash +cargo build --release +time ./target/release/word_correction +``` +to test. In MacBook Air M2, My test result is +```bash +> time ./target/release/word_correction +./target/release/word_correction 0.13s user 0.07s system 97% cpu 0.213 total +``` diff --git a/correrified_words.txt b/correrified_words.txt new file mode 100644 index 0000000..db6fcd7 --- /dev/null +++ b/correrified_words.txt @@ -0,0 +1,6167 @@ +0004 I go/am/want/work +0005 am I/the/only +0007 your friend/happiness/shoes +0008 name after/class/number +0010 my computer/parents/he/her +0012 bye bye/see/wave/say +0013 Miss Mrs/Mr/yours/polite +0016 you are/he/she/I +0017 are you/they/we +1338 is he/she/it +0020 good afternoon/job/well/fine/nice +0021 afternoon good/evening/noon/morning +0023 morning good/afternoon/noon/midnight +0025 night good/midnight/morning/noon +0027 this is/that/like +1340 that this/these/is/like +0028 Mr Miss/polite/gentle/custom +0030 do you/me/her/he +0031 nice good/better/well/people +0032 meet with/see/watch/walk +0034 too much/also/yet/many +0037 how much/many/fun +0039 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tree/animal/grass/lake +1304 hull fruit/nut/grape/banana +1306 mountain hill/climb/Qomolangma/peak +1311 village country/city/town/house +1312 house home/expensive/door/window +1314 bridge car/river/arch/boat +1315 building mansion/house/hotel/government +1317 sea fish/wave/swim/ship +1319 puppet thread/wood/game/show +1321 hide shadow/seek/child/afraid +1322 seek treasure/see/find/investigate +1324 find out/seek/surprise/experiment +1328 schedule daytime/calendar/curriculum/class +1332 throw exception/trash/rubbish/ball +1334 naughty child/kindergarten/cry/bully +1335 feature character/temperament/nature/inherent/ diff --git a/src/main.rs b/src/main.rs new file mode 100644 index 0000000..86ded36 --- /dev/null +++ b/src/main.rs @@ -0,0 +1,95 @@ +#![doc = include_str!("../README.md")] + +use levenshtein::levenshtein; +use std::fs::{File, read_to_string}; +use std::io::Write; + +fn parse_line(file: &str) -> Vec { + read_to_string(file) + .expect(format!("No {} found", file).as_str()) + .lines() + .map(String::from) + .collect() +} + +fn parse_words(file: &str) -> Vec> { + let words_line = parse_line(file); + let mut words = Vec::new(); + + for word in words_line.iter() { + let word_chars = word + .as_str() + .split(&['/', ' '][..]) + .map(String::from) + .collect::>(); + + words.push(word_chars); + } + words +} + +fn correrify<'a>(word: &'a str, dict: &'a Vec) -> &'a str { + if let Ok(_) = dict.binary_search(&word.to_string()) { + return word; + } + + let mut temp_min = (usize::MAX, ""); + for check_word in dict.iter() { + let distance = levenshtein(word, check_word.as_str()); + + if distance <= 1 { + return check_word; + } + if distance < temp_min.0 { + temp_min = (distance, check_word); + } + } + + temp_min.1 +} + +fn select_word_correrify(words: &Vec>, dict: &Vec) -> Vec> { + let mut word_correrified = Vec::new(); + for word_line in words.iter() { + assert!(word_line[0].len() == 4); + assert!(word_line[0].chars().all(|c| c.is_numeric())); + + word_correrified.push( + vec![word_line[0].clone()] + .into_iter() + .chain( + word_line + .iter() + .skip(1) + .map(|word| correrify(word, dict).to_string()) + .collect::>(), + ) + .collect::>(), + ); + } + + word_correrified +} + +fn write_correrified_words(words: &Vec>) { + let mut file = File::create("correrified_words.txt").expect("Unable to create file"); + for word_line in words.iter() { + writeln!( + file, + "{} {} {}", + word_line[0], + word_line[1], + word_line[2..].join("/") + ) + .expect("unable to write to file"); + } +} + +fn main() { + let mut dict = parse_line("vocabulary.txt"); + dict.sort_unstable(); // sort the dictionary to accelerate the search + let words = parse_words("words.txt"); + let word_correrified = select_word_correrify(&words, &dict); + + write_correrified_words(&word_correrified); +} diff --git a/vocabulary.txt b/vocabulary.txt new file mode 100644 index 0000000..d5c1e12 --- /dev/null +++ b/vocabulary.txt @@ -0,0 +1,3242 @@ +secondly +temperament 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