A bit-level text compression scheme based on the ACW algorithm

Al-Bahadili, Hussein; Hussain, Shakir M.

doi:10.1007/s11633-010-0123-6

Cited by 20 publications

(14 citation statements)

References 17 publications

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“…This section presents a description of the data compression scheme that shall be used in this search engine model, namely, the adaptive character wordlength (ACW(n,s)) scheme [14]. This scheme is based on the adaptive character wordlength (ACW(n)) algorithm [15], therefore, it will be described first.…”

Section: The Data Compression Schemementioning

confidence: 99%

“…A data compression scheme that satisfies this requirement is the recently developed adaptive character wordlength (ACW(n,s)) scheme [14,15], therefore, it will be used in this work. Recent investigations on using this scheme for text compression demonstrated an excellent performance in comparison with many widely-used data compression algorithms and state-of-the-art tools [14,15]. This paper is organized in 7 sections.…”

Section: Introductionmentioning

confidence: 99%

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A web search engine model based on index-query bit-level compression

Al-Bahadili

Al-Saab

Naoum

et al. 2010

Proceedings of the 1st International Conference on Intelligent Semantic Web-Services and Applications

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In this paper, we propose a new web search engine model based on index-query bit-level compression. The model incorporates two bit-level compression layers both implemented at the backend processor (server) side, one layer resides after the indexer acting as a second compression layer to generate a double compressed index, and the second layer be located after the query parser for query compression to enable bit-level compressed index-query search. This contributes to reducing the size of the index file as well as reducing disk I/O overheads, and consequently yielding higher retrieval rate and performance. The data compression scheme used in this model is the adaptive character wordlength (ACW(n,s)) scheme, which is an asymmetric, lossless, bit-level scheme that permits compressed index-query search. Results investigating the performance of the ACW(n,s) scheme is presented and discussed.

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Section: The Data Compression Schemementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A web search engine model based on index-query bit-level compression

Al-Bahadili

Al-Saab

Naoum

et al. 2010

Proceedings of the 1st International Conference on Intelligent Semantic Web-Services and Applications

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, the decoding speed of this technique is relatively slow. Bahadili and Hussain (2010) presented a new bit level adaptive data compression technique based on ACW algorithm, which is shown to perform better than many widely used compression algorithms in terms of compression ratio. Hermassi et al (2010) showed how a symbol can be coded by more than one codeword having the same length.…”

Section: Banetley Et Al (1986) Introduced a New Compression Techniqumentioning

confidence: 99%

Balancing decoding speed and memory usage for Huffman codes using quaternary tree

Habib

Rahman

2017

Appl Inform

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“…Actually the importance of lossless data compression is it doesn't allow any data loss. Even if a single bit of data is lost after decoding, that determines the file is corrupted [3] [4].The most attractive part of data compression is compressing data in a database system. The performance is immensely improved because smaller size of physical data are needed to be moved for any operation on the database [1] [2].…”

Section: Introductionmentioning

confidence: 99%

An Efficient Text Database Compression Technique using 6 Bit Character Encoding by Table Look Up

Mahmood¹,

Latif²,

Islam³

2017

IJCA

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Character encoding determines a term which represents a repertoire of characters by some kind of encoding technique. It covers a huge area of applications such as data communication, storage of data, textual data transmission and database technology. In this paper, a new technique of compression for text data is proposed which encodes a character by 6 bits namely 6 -Bit Encoding (6BE). Actually the working method of this technique is encoding an 8 bit character by 6 bits. This technique works with the characters which are printable. For encoding a character to 6 bit, it uses a lookup table. Firstly, it divides the characters into 4 sets and then it uses the location of characters uniquely to encode by 6 bits. By this procedure 8 bit characters are converted into 6 bits by this 6BE technique. At First, this technique on simple text. It is found that, the 6BE technique can able to compress the original text by 25%. After that this 6BE technique is used in proper database technology by compressing the text data in a table of a database. The 6BE is able to compress as well as decompress the original data with the help a lookup table. The reverse technique is also detailed for decompression to get back the original table. The outcome of 6BE technique is also applied to compress again by the known algorithm Huffman and LZW. The experimental result shows promising performance. The technique is further discussed by some examples and descriptions.

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A bit-level text compression scheme based on the ACW algorithm

Cited by 20 publications

References 17 publications

A web search engine model based on index-query bit-level compression

A web search engine model based on index-query bit-level compression

Balancing decoding speed and memory usage for Huffman codes using quaternary tree

An Efficient Text Database Compression Technique using 6 Bit Character Encoding by Table Look Up

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