N-gram Language Model for Autocomplete (Python)

Description:

This Python script implements a basic N-gram language model for text autocompletion. It allows users to enter a sequence of words, and the model suggests the most likely next word based on the frequency of word n-grams observed in the training data.

Features:

• Processes and cleans Twitter data using regular expressions and tokenization.
• Handles out-of-vocabulary (OOV) words using an unknown token ("").
• Builds N-gram models (unigrams, bigrams, trigrams, etc.) up to a configurable maximum N.
• Calculates probabilities for next words using Laplace smoothing.
• Provides suggestions based on multiple N-gram models, allowing the user to choose the best fit.

Usage:

1. Save the script as n_gram_autocomplete.py.
2. Modify the file_path variable in the script to point to your Twitter data file (.txt format).
3. Run the script: python n_gram_autocomplete.py.
4. Enter a sequence of words and press Enter. The script will suggest the most likely next word(s).