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A dictionary coder, also sometimes known as a substitution coder, is a class of lossless data compression algorithms which operate by searching for matches between the text to be compressed and a set of strings contained in a data structure (called the 'dictionary') maintained by the encoder. When the encoder finds such a match, it substitutes ...
Examples: An empty string is encoded as 0:. The string "bencode" is encoded as 7:bencode. Lists are encoded as l<elements>e. Begins with l and ends with e. Elements are bencoded values concatenated without delimiters. Examples: An empty list is encoded as le. A list containing the string "bencode" and the integer -20 is encoded as l7:bencodei-20ee.
Incremental encoding is widely used in information retrieval to compress the lexicons used in search indexes; these list all the words found in all the documents and a pointer for each one to a list of locations. Typically, it compresses these indexes by about 40%.
The move-to-front (MTF) transform is an encoding of data (typically a stream of bytes) designed to improve the performance of entropy encoding techniques of compression.When efficiently implemented, it is fast enough that its benefits usually justify including it as an extra step in data compression algorithm.
Sparse dictionary learning (also known as sparse coding or SDL) is a representation learning method which aims to find a sparse representation of the input data in the form of a linear combination of basic elements as well as those basic elements themselves. These elements are called atoms, and they compose a dictionary.
In computer science, an associative array, map, symbol table, or dictionary is an abstract data type that stores a collection of (key, value) pairs, such that each possible key appears at most once in the collection.
Each dictionary entry is of the form dictionary[...] = {index, token}, where index is the index to a dictionary entry representing a previously seen sequence, and token is the next token from the input that makes this entry unique in the dictionary. Note how the algorithm is greedy, and so nothing is added to the table until a unique making ...
A high-level view of the encoding algorithm is shown here: Initialize the dictionary to contain all strings of length one. Find the longest string W in the dictionary that matches the current input. Emit the dictionary index for W to output and remove W from the input. Add W followed by the next symbol in the input to the dictionary. Go to Step 2.