Analysis of Wordle Game Mechanism Based on LSTM and MLP
DOI:
https://doi.org/10.54097/hset.v41i.6818Keywords:
Three-layer LSTM, multiple sequence prediction model, NLP model, MLP model.Abstract
This paper uses data analysis, deep learning and natural language processing techniques to study the difficulty and result distribution of word guessing based on the Wordle game mechanism. First, a three-layer LSTM model is established to predict the number of reported results, and the correlation between word factors and guessing difficulty is analyzed. Next, a multi-sequence LSTM model combined with NLP models is established to predict the result distribution of specific words at specific times. Finally, an MLP classification model is built to classify the difficulty of words.
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