Fast Heuristic Detection of Offensive Words in Wordwheel Puzzles
Abstract
Offensive words appear in Wordwheel-type puzzles with a high frequency. Previous approaches to eliminating these words have focused largely on eliminating puzzles that might give rise to an offensive word. This work presents a fast, heuristic approach to detecting an offensive word within a puzzle. After a preprocessing stage, the detection occurs with a single bitwise operation on a 64-bit word. Tests show that as long as there are at least 3 taboo words possible in a puzzle, the heuristic approach is faster than a depth-first search of the puzzle. In addition to being fast, the approach is guaranteed to detect all offensive words, and has a low false positive rate.
Cite
Text
Blum and Parry. "Fast Heuristic Detection of Offensive Words in Wordwheel Puzzles." AAAI Conference on Artificial Intelligence, 2022. doi:10.1609/AAAI.V36I11.21549Markdown
[Blum and Parry. "Fast Heuristic Detection of Offensive Words in Wordwheel Puzzles." AAAI Conference on Artificial Intelligence, 2022.](https://mlanthology.org/aaai/2022/blum2022aaai-fast/) doi:10.1609/AAAI.V36I11.21549BibTeX
@inproceedings{blum2022aaai-fast,
title = {{Fast Heuristic Detection of Offensive Words in Wordwheel Puzzles}},
author = {Blum, Anand D. and Parry, R. Mitchell},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2022},
pages = {12721-12726},
doi = {10.1609/AAAI.V36I11.21549},
url = {https://mlanthology.org/aaai/2022/blum2022aaai-fast/}
}