A Self-Learning and Lossless Dictionary-Based Compression Algorithm

This paper describes, analyzes, and compares a self-learning, dictionary-based compression algorithm with other existing algorithms. Upon comparison, this algorithm has been observed to achieve compression levels close to $85 \%$. As this is a self-learning algorithm, it solves the problem of some static, dictionary-based compression algorithms not being able to compress the entries absent in the dictionary. It also solves the problem of some algorithms transmitting the dictionary with each file (as the dictionary can be separated from the compressed file and self-hosted with a server, which can then be accessed by exposing it to the internet or the intranet (if used for organizational purposes)), thereby reducing the overall size of a file considerably.