In this paper, a new compression method for constant removal from very large scientific and statistical databases is presented. The new method combines the best features from several classical constant removal compression methods. The result, both analytical and expprimental, shows that the method is superior to these popular methods in terms of compression effectiveness and eficient searching on the. compressed data. In addition to the development, analysis and validation of this new method, this paper also presents analysis of several traditional constant removal methods for the purpose of analytic comparison. A large collection of experiments have been designed and run to observe and validate the behavior of the compression methods. Another contribution of the paper is that performance characteristics are identified for different compression methods under diierent data properties sssumptions. The result can be used as a bssis of selecting compression methods by matching the propert...
Jianzhong Li, Doron Rotem, Harry K. T. Wong