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Author Moffat, A. ♦ Anh, V.N.
Sponsorship Brandeis Univ
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2005
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Binary codes ♦ Decoding ♦ Probability distribution ♦ Entropy ♦ Costs ♦ Testing ♦ Dictionaries ♦ Application software ♦ Computer science ♦ Software engineering
Abstract In many applications of compression, decoding speed is at least as important as compression effectiveness. For example, the large inverted indexes associated with text retrieval mechanisms are best stored compressed, but a working system must also process queries at high speed. Here we present two coding methods that make use of fixed binary representations. They have all of the consequent benefits in terms of decoding performance, but are also sensitive to localized variations in the source data, and in practice give excellent compression. The methods are validated by applying them to various test data, including the index of an 18 GB document collection.
Description Author affiliation: Dept. of Comput. Sci. & Software Eng., Melbourne Univ., Vic., Australia (Moffat, A.; Anh, V.N.)
ISBN 0769523099
ISSN 10680314
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2005-03-29
Publisher Place USA
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 161.04 kB
Page Count 10
Starting Page 133
Ending Page 142


Source: IEEE Xplore Digital Library