Short text compression for smart devices

Short text compression is a great concern for data engineering and management. The rapid use of small devices especially, mobile phones and wireless sensors have turned short text compression into a demand-of-the-time. In this paper, we propose an approach of compressing short English text for smart devices. The prime objective of this proposed technique is to establish a low-complexity lossless compression scheme suitable for smart devices like cellular phones and PDAs (personal digital assistants) having small memory and relatively low processing speed. The main target is to compress short messages up to an optimal level, which requires optimal space, consumes less time and low overhead. Here we propose a new static-statistical context model to obtain the compression. We also propose an efficient probabilistic distribution based content-ranking scheme for training the statistical model. We analyze the performance of the proposed scheme as well as the other similar existing schemes with respect to compression ratio, computational complexity and compression-decompression time. The analysis shows that, the required number of operations for the proposed scheme is less than that of other existing systems. The experimental results of the implemented model gives better compression for small text files using optimum resources. The obtained compression ratio indicates a satisfactory performance with reduced memory requirements and lower complexity. The compression time is also lower because of computational simplicity. In overall analysis, the simplicity of computational requirement encompasses the compression effective and efficient.