Improving semistatic compression via phrase-based modeling

In recent years, new semistatic word-based byte-oriented text compressors, such as Tagged Huffman and those based on Dense Codes, have shown that it is possible to perform fast direct search over compressed text and decompression of arbitrary text passages over collections reduced to around 30–35% of their original size. Much of their success is due to the use of words as source symbols and a byte-oriented target alphabet. This approach broke with traditional statistical compressors, which use characters as source symbols and a bit-oriented target alphabet.