Tabular Numeric Data Compression Using Base-14 Row Encoding
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Solution Overview
Problem
Current data compression systems, such as DEFLATE, ZIP, and RAR, are insufficient in reducing the size of tabular numeric data, leading to high storage and processing costs due to inadequate compression ratios.
Innovation Solution
A system and method for lossless compression of tabular numeric data that converts tables of integers into base-14 strings, concatenates them, and writes pairs of characters into a byte array, reducing data size without data loss, which can be further enhanced by combining with other compression algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If existing compression systems (DEFLATE, ZIP, RAR) are used on tabular numeric data, then general compression is achieved, but compression ratios are insufficient
Solution Approach 1:
The patent applies parameter changes by converting numeric data from standard base-10 representation to base-14 representation. This fundamental parameter change in the numerical system allows for more efficient encoding of tabular data, achieving compression ratios of 40-43.5% which significantly improves upon traditional compression methods while maintaining lossless compression.
Solution Approach 2:
The patent segments the tabular numeric data by processing it row-by-row and applying differential encoding where each row is rewritten based on the difference from the preceding row. This segmentation approach exploits the temporal or sequential correlation between rows, allowing for more effective compression compared to treating the entire dataset as a single block.
2Quantity of substance
If tabular data is stored in standard formats, then ease of processing is maintained, but storage costs are high
Solution Approach 1:
The patent changes the representation parameter from standard decimal to base-14 encoding, which reduces the number of digits required to represent the same numeric values. This parameter transformation achieves significant storage space reduction while the systematic approach to conversion and the use of standard byte array structures maintain reasonable processing simplicity.
3Quantity of substance
If compression is applied to reduce data size, then storage and transfer costs decrease, but processing complexity increases
Solution Approach 1:
The patent implements a relatively simple parameter change from base-10 to base-14 conversion with differential row encoding. This approach achieves effective compression without requiring complex algorithmic structures, making the compression and decompression processes computationally efficient and easy to implement compared to sophisticated compression algorithms.
Data Source
AI summary
Systems and methods for lossless compression of tabular numeric data are provided. The system can include one or more data compression servers executing data compression system code to compress the tabular numeric data, a storage database to store the compressed tabular numeric data, and one or more data decompression servers to decompress the tabular numeric data for use. The one or more data compression servers, the storage database, and the one or more data decompression servers can communicate via a communication network. The system can receive the uncompressed tabular numeric data from one or more data generation systems, processes the uncompressed tabular numeric data with the data compression system code, and generate a compressed table of numeric information, which can be stored in the database, or later decompressed by the one or more data decompression servers.