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DOI: 10.14569/IJACSA.2021.0120452
PDF

Speeding up Natural Language Text Search using Compression

Author 1: Majed AbuSafiya

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 4, 2021.

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Abstract: Text search is a well-known problem in computer science where the valid shifts of a pattern P in a text string T are found. This paper shows how to speed up text search by searching for P in a compressed version of T. A fast compression algorithm was designed for this aim. This algorithm is based on the assumption that T is restricted to the letters of a single natural language. Relying on this assumption, a letter, in T or P, is encoded into a single byte instead of the two-byte unicode which shortens the string on which a text search algorithm works. The main disadvantage of this approach is the restriction of the alphabet of T to be from a single natural language. However, wide range of text documents comply to this assumption. Another issue is the overhead that is required to compress P and T, but it was found that the proposed compression algorithm is so fast such that its run-time can be paid for and still save text search time. Different approaches to store compressed T are also explored. The conducted experimental study showed that this approach does actually reduce the text search time.

Keywords: Text compression; text search; unicode

Majed AbuSafiya, “Speeding up Natural Language Text Search using Compression” International Journal of Advanced Computer Science and Applications(IJACSA), 12(4), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120452

@article{AbuSafiya2021,
title = {Speeding up Natural Language Text Search using Compression},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120452},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120452},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {4},
author = {Majed AbuSafiya}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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