The concept of DAWGs is based on: Blumer, A. et al. (1985). The smallest automation recognizing the subwords of a text. Theoretical Computer Science, 40, 31–55.

Directed Acyclic Word Graph implementation

learning haskell

Simple implementation of DAFSA minimization using Revuz's algorithm.

Projet de structures de données et algorithmes, L2S4 Unistra 2021

Port of dawgdic C++ library to Java.

Pure-python reader for DAWGs created by dawgdic C++ library or DAWG Python extension. Fork of https://github.com/pytries/DAWG-Python

Pure-python reader for DAWGs on CircuitPython compatible boards.

Fork from https://code.google.com/archive/p/dawgdic/

MinHash and LSH Based Store and Query.

this is a website about dogs.

Implementation of Word Trie (directed acyclic word graph), which can be used while building basic chat-bots with simple mechanism with pre-defined responses for specific questions.

fertile eyeball butterfly

This code work is spotting rhyming characters from rhyming words using the concept of DAFSA.

Scrabble game implemented using a microservices architecture. Technology stack: Spring (backend), Angular (frontend).

Deterministic acyclic finite state automaton in crystal

(WIP) 文章からのキーワード抽出や文字列のあいまいマッチなどに使えるデータ構造

OCR reading assistant with opencv, Tesseract, kraken, DAWGs and a splay tree

A crossword game engine

The project leverages a combination of models and methods to predict missing letters in a word, enhancing the Hangman gameplay experience. The core methodologies include a Bidirectional LSTM (BiLSTM) model, a Directed Acyclic Word Graph (DAWG) structure, and a BERT model.