TY - GEN

T1 - Let Sleeping Files Lie: Pattern Matching in Z-Compressed Files

AU - Amihood, A.

AU - Farach, M.

AU - Benson, G.

N1 - Place of conference:Arlington, Virginia, USA

PY - 1994

Y1 - 1994

N2 - The current explosion of stored information necessitates a new model of pattern matching, that ofcompressed matching. In this model one tries to find all occurrences of a pattern in a compressed text in time proportional to the compressed text size,i.e., without decompressing the text. The most effective general purpose compression algorithms areadaptive, in that the text represented by each compression symbol is determined dynamically by the data. As a result, the encoding of a substring depends on its location. Thus the same substring may “look different” every time it appears in the compressed text. In this paper we consider pattern matching without decompression in the UNIX Z-compression. This is a variant of the Lempel–Ziv adaptive compression scheme. Ifnis the length of thecompressedtext andmis the length of the pattern, our algorithms find the first pattern occurrence in timeO(n+m2) orO(n log m+m). We also introduce a new criterion to measure compressed matching algorithms, that ofextra space. We show how to modify our algorithms to achieve a trade-off between the amount of extra space used and the algorithm's time complexity.

AB - The current explosion of stored information necessitates a new model of pattern matching, that ofcompressed matching. In this model one tries to find all occurrences of a pattern in a compressed text in time proportional to the compressed text size,i.e., without decompressing the text. The most effective general purpose compression algorithms areadaptive, in that the text represented by each compression symbol is determined dynamically by the data. As a result, the encoding of a substring depends on its location. Thus the same substring may “look different” every time it appears in the compressed text. In this paper we consider pattern matching without decompression in the UNIX Z-compression. This is a variant of the Lempel–Ziv adaptive compression scheme. Ifnis the length of thecompressedtext andmis the length of the pattern, our algorithms find the first pattern occurrence in timeO(n+m2) orO(n log m+m). We also introduce a new criterion to measure compressed matching algorithms, that ofextra space. We show how to modify our algorithms to achieve a trade-off between the amount of extra space used and the algorithm's time complexity.

UR - https://scholar.google.co.il/scholar?q=Let+Sleeping+Files+Lie%3A+Pattern+Matching+in+Z-Compressed+Files&btnG=&hl=en&as_sdt=0%2C5

M3 - Conference contribution

BT - 5th Annual ACM-SIAM Symposium On Discrete Algorithms (SODA)

ER -