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October 1, 2006ACM Transactions on Algorithms79 citations

When indexing equals compression

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LFLuca FoschiniRGRoberto GrossiAGAnkur Gupta

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Abstract

We report on a new experimental analysis of high-order entropy-compressed suffix arrays, which retains the theoretical performance of previous work and represents an improvement in practice. Our experiments indicate that the resulting text index offers state-of-the-art compression. In particular, we require roughly 20% of the original text size---without requiring a separate instance of the text. We can additionally use a simple notion to encode and decode block-sorting transforms (such as the Burrows--Wheeler transform), achieving a compression ratio comparable to that of bzip2. We also provide a compressed representation of suffix trees (and their associated text) in a total space that is comparable to that of the text alone compressed with gzip.

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Cite This Study

Foschini et al. (2006) studied this question.

synapsesocial.com/papers/6a6398424f5ef41b946ae01fhttps://doi.org/10.1145/1198513.1198521
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