How do Jacob Ziv and Abraham Lempel’s compression methods use repeated text blocks?
Consider a simple telephone conversation: A person (message source) speaks into a telephone receiver (encoder), which converts the sound of the spoken word into an electrical signal. This electrical signal is then transmitted over telephone lines (channel) subject to interference (noise). When the signal reaches the telephone receiver (decoder) at the other end of the line it is converted back into vocal sounds. Finally, the recipient (message receiver) hears the original message.
The Lempel-Ziv algorithm, developed by Abraham Lempel and Jacob Ziv, uses an adaptive, dictionary-based approach to compress data by leveraging repeated sequences of text.12
Instead of relying on pre-defined probabilities, the algorithm dynamically constructs a "codebook" or dictionary from the sequences it encounters within the data itself. When a block of text reappears, the algorithm replaces the repeated sequence with a reference—typically a pointer or number indicating where that specific block occurred previously and its length—rather than re-transmitting the original text.123
As the encoder processes the input, it continuously updates this dictionary. If a sequence is encountered that is not yet in the dictionary, the encoder transmits the code for the known prefix plus an extra bit or value to represent the new character, subsequently adding the new, longer sequence to the dictionary for future use. This method allows the compression to adapt to the specific patterns and vocabulary of the source text, making it highly efficient for general data compression.132