Integer-Based Text Graphic Encoding for NLP Efficiency
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Solution Overview
Problem
Current methods for numerically processing words and texts in natural language processing are inefficient, particularly due to the use of long one-hot vectors, which hinder machine learning and visualization.
Innovation Solution
A method that converts text into a two-dimensional graphic representation by encoding each character into integers, transforming them into binary numbers, separating even and odd bits, and plotting these as Cartesian coordinates to create a unique encoded image, allowing for efficient machine recognition and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If long one-hot vectors are used to represent words and texts, then complete character information is preserved, but processing efficiency and machine learning performance deteriorate
Solution Approach 1:
The patent segments the text representation by separating even and odd bits from the binary form of character codes, creating two distinct integer sequences. This segmentation reduces the dimensionality from long one-hot vectors to shorter integer sequences while preserving the complete character information through the bit separation process.
Solution Approach 2:
The patent changes the parameter representation from binary character codes to decimal integer sequences by transforming the binary string into decimal format. This parameter transformation compresses the data representation while maintaining information completeness, converting long one-hot vectors into more compact integer-based representations.
2Loss of information
If long one-hot vectors are used for text representation, then all character details are maintained, but visualization and machine recognition become difficult
Solution Approach 1:
The patent segments the binary representation into even and odd bit sequences, which are then converted to decimal integer sequences. This segmentation creates a more structured and interpretable format that enhances machine recognition and visualization capabilities while preserving all character details through the reversible transformation process.
Solution Approach 2:
The patent creates a copied representation of the text using integer sequences derived from bit separation. This copy maintains all character information through the transformation but presents it in a format that is easier for machines to process and visualize, separating the information into manageable integer sequences rather than long vectors.
3Adaptability or versatility
If traditional text encoding methods are used, then compatibility with existing systems is maintained, but storage and transmission efficiency deteriorate
Solution Approach 1:
The patent changes the parameter format from binary character codes to decimal integer sequences through bit separation and conversion. This parameter transformation reduces the data size for storage and transmission while maintaining compatibility with existing systems through the use of standard integer types and arithmetic operations.
Data Source
AI summary
Aspects of the subject disclosure may include, for example, a method of transforming, by a processing system comprising a processor, text comprising a series of characters into a graphic representation, wherein the graphic representation comprises a series of dots arranged in a two-dimensional pattern, wherein the two-dimensional pattern comprises two dots per character, and wherein each dot in the series of dots is one unit away from a preceding dot; and plotting, by the processing system, the series of dots on a two-dimensional graph, thereby creating a unique encoded image of the text. Other embodiments are disclosed.