Compression of indexes with full positional information in very large text databases
Gordon S. Linoff, Craig Stanfill · 1993
This paper describes a combination of compression methods which may be used to reduce the size of inverted indexes for very large text databases. These methods are Prefix Omission, Run-Length Encoding, and a novel family of numeric representations called n-s coding. Using these compression methods on two different text sources (the King James Version of the Bible and a sample of Wall Street Journal Stories), the compressed index occupies less than 40% of the size of the original text, even when both stopwords and numbers are included in the index. The decreased time required for I/O can almost fully compensate for the time needed to uncompress the postings. This research is part of an effort to handle very large text databases on the CM-5, a massively parallel MIMD supercomputer.