An Optimized Integer Representation through a Novel Numeric Encoding for Textual Data Compression - Harshali Patil, Poonam Joshi,Tarunima Mukherjee, Kanak Pandit (International Journal of Intelligent Systems and Applications in Engineering, 2024)
The objective of this paper is to introduce a new variable sized integer encoding technique for file compression. The paper aims to compare the performance of the proposed method with established codes like Elias Gamma, Elias Delta, and Golomb. The study also seeks to examine the impact of varying log base values on compression ratio and runtime efficiency. The proposed method utilizes radix conversion and the Burrows Wheeler Transform for file compression. Performance comparison is conducted on the Calgary corpus, which includes both text and binary files. Existing codes like Elias Gamma, Elias Delta, and Golomb are executed on the files before evaluating the proposed code. Graphs are used to analyze the impact of log base values on compression ratio, while runtime efficiency is assessed. The proposed compression code achieves varied compression ratios (1.67 to 1.87) at radix r=4, highlighting its effectiveness over existing algorithms. A non-linear relationship between the log base and compression ratio is observed, plateauing as the log base increases. Runtime varies among files, with ’bib1’ at the longest time (6.41 seconds) and ’obj1’ the shortest (0.09 seconds). A positive correlation exists between the number of data points (n) and runtime, while a negative correlation is seen between ’n’ and compression ratio, indicating lower ratios for larger ’n’ files. Comparing its performance with established codes provides a benchmark for evaluation. Analyzing compression ratio trends and runtime efficiency offers insights into the effectiveness of the proposed method, adding to its novelty.