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@article{152358,
        author = {Kajal Saluja and Renuka Arora},
        title = {STATISTICAL ADAPTIVE ARITHMETIC CODING},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {3},
        pages = {251-255},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=152358},
        abstract = {Data Compression is an area that needs to be given almost attention to is text quality assessment. Different methodologies have been defined for this purpose. Hence choosing the best machine learning algorithm is important. In addition to different compression technologies and methodologies, the selection of a good data compression tool is most important. There is a complete range of different data compression techniques available both online and offline working such that it becomes really difficult to choose which technique serves the best. Here comes the necessity of choosing the right method for text compression purposes and hence an algorithm that can reveal the best tool among the given ones. A data compression algorithm is to be developed which consumes less time while provides more compression ratio as compared to existing techniques. In this paper, we represent a hybrid approach to compress the text data. This hybrid approach is the combination of the Dynamic Bit reduction method and Huffman coding. },
        keywords = {Text data compression, Dynamic Bit Reduction method, Huffman coding, lossless data compression.},
        month = {},
        }