Encoded Text Type Management for Multilingual Storage Efficiency
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Solution Overview
Problem
Existing character encoding methodologies for displaying multiple languages on computing devices inefficiently use storage space, as they vary significantly in data requirements, leading to suboptimal storage and resource utilization.
Innovation Solution
An encoding methodology that utilizes predefined prefixes and a mapping table, allowing for efficient storage by calculating a continuous word count and managing encoding spaces below a threshold, thereby optimizing storage usage across different encoding types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional character encoding methodologies (UTF-8, UTF-16) are used to display multiple languages, then language compatibility is improved, but storage space efficiency deteriorates
Solution Approach 1:
The patent segments text data into different encoded text data types (first encoded text data type, second encoded text data type, etc.) and manages each segment with appropriate encoding rules. This allows the system to apply different storage efficiencies to different language segments while maintaining overall compatibility
Solution Approach 2:
The patent changes the encoding parameters dynamically by identifying encoded text data types and selecting appropriate bit representations (first set of bits, second set of bits, etc.). This enables the system to optimize storage space by using fewer bits for certain encoding types while maintaining language compatibility through proper parameter selection
2Measurement precision
If encoded text data types with varying data requirements are used, then language representation accuracy is improved, but storage utilization deteriorates
Solution Approach 1:
The patent implements dynamic encoding management by continuously monitoring and adjusting the number of encoding spaces used. The system can adaptively switch between different encoded text data types and bit representations based on the actual language representation needs, optimizing both accuracy and storage utilization in real-time
Data Source
AI summary
Disclosed aspects relate to encoded text data management using a set of encoded text data types. A first set of bits which indicates a first encoded text data type may be identified. A second set of bits which indicates a first quantitative size of a third set of bits for a first set of text data of the first encoded text data type may be identified. Using both the first set of bits and the second set of bits, an encoded data management operation may be executed with respect to the third set of bits for the first set of text data of the first encoded text data type.