AIMCS: An Artificial Intelligence based Method for Compression of Short Strings
Masoud Abedi, Mohammadreza Pourkiani · 2020
In recent years, the use of short texts in data communications has dramatically increased. In order to reduce the bandwidth utilization and cost, new compression methods must be applied to short texts. In this paper, we propose an artificial intelligence-based lossless compression algorithm which aims to reduce the size of messages over the network. Evaluating this algorithm, we applied it on tiny-strings (strings with an average length of 160 characters) and the achieved results show that our proposed approach (AIMCS) reduces the size of data significantly. Comparing our algorithm with LZW and Huffman methods also indicates that in the compression process of strings, our method provides better performance in terms of compression rate. In contrast, the compression time increases, which is insignificant comparing to transmission time when real-time text transmission is required.