Intelligent Word Prediction
Advanced Autocorrect System using Natural Language Processing
Experience the power of machine learning in text prediction and correction. This system uses frequency analysis and similarity algorithms to suggest the most relevant words.
Text Analysis
Analyzes word frequency patterns
Smart Correction
Intelligent autocorrect suggestions
Fast Processing
Real-time word prediction
Interactive Demo
Word Predictions
Enter a word above to see intelligent predictions and corrections.
About This Project
Frequency Analysis
Analyzes word frequency from text data to understand common word patterns and usage statistics.
Similarity Calculation
Uses Jaccard distance to measure similarity between words and find the closest matches.
Probability Scoring
Calculates relative frequency probabilities to rank word suggestions by likelihood.
Smart Ranking
Combines similarity and probability scores to provide the most relevant word suggestions.
How It Works
Text Processing
The system reads text data, converts it to lowercase, and extracts individual words using regular expressions.
words = re.findall('\w+', data.lower())
Frequency Analysis
Creates a frequency dictionary using Counter to track how often each word appears in the dataset.
word_freq_dict = Counter(words)
Probability Calculation
Calculates relative frequency probabilities for each word based on total word count.
prob = freq[word] / total_words
Similarity Matching
Uses Jaccard distance with 2-grams to find words similar to the input and ranks them by probability.
similarity = 1 - jaccard_distance(word1, word2)