An Implementation of Efficient Text Data Compression
Virendra Kumar Swarnkar1,  K. J. Satao2
1Virendra Kumar Swarnkar, Computer Science & Engineering; Bharti College of Engineering & Technology, Durg, Chhattisgarh, India.
2Prof. K. J. Satao, Computer Science & Engineering; Head, Department of Information Technology, Rungta College of Engineering & Technology, Bhilai, Chhattisgarh, India.
Manuscript received on November 27, 2013. | Revised Manuscript received on December 13, 2013. | Manuscript published on December 30, 2013. | PP: 1-5 | Volume-3, Issue-2, December 2013. | Retrieval Number:  B2517123213/2013©BEIESP

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Abstract: The size of data related to a wide range of applications is growing rapidly. Typically a character requires 1 Byte for storing. Compression of the data is very important for data management. Data compression is the process by which the physical size of data is reduced to save on memory or improve traffic speeds on a website. The purpose of data compression is to make a file smaller by minimizing the amount of data present. When a file is compressed, it can be reduced to as little as 25% of its original size which makes it easier to send to others over the internet. Data compression may take extensions such as zip, rar, ace, and BZ2. It is normally done using special compression software. Compression serves both to save storage space and to save transmission time. The aim of compression is to produce a new file, as short as possible, containing the compressed version of the same text. Grand challenges such as the human generated project involve very large distributed databases of text documents, whose effective storage and communication requires a major research and development effort. Several text compression schemes have been introduced for reducing storage space and transfer time via a computer network. The aim of this paper is to introduce a scheme for text data compression which will take less storage space, will yield better compression rate and compression ratio.
Keywords: Data compression, Data decompression, Compression algorithms, Compression ratio, Compression rate.