PPM (Prediction by Partial Matching)

Prediction by Partial Matching (PPM) is a data compression technique that analyzes the context of previous data to predict what comes next. It looks at recent sequences of symbols and uses their patterns to estimate the probability of subsequent symbols, allowing it to encode data more efficiently. Essentially, PPM adapts as it processes data, learning and leveraging patterns to achieve better compression. It’s used in contexts like text and language compression, where understanding the likelihood of certain characters or words based on prior context improves overall efficiency.