Synonym Determination Among N-grams Using Temporal Histograms
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Solution Overview
Problem
Existing systems face challenges in discerning concepts of interest in large volumes of human-generated messages, such as text messages and social media posts, due to variations in wordings and spellings used by different individuals.
Innovation Solution
A computing system that determines synonyms by parsing messages into n-grams, generating temporal histograms, correlating these histograms, computing character-based distance measures, and selecting synonyms based on correlation and distance metrics, utilizing engines such as temporal histogram, correlation, distance measurement, and synonym determination engines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual reading of messages is used to discern concepts, then understanding accuracy is maintained, but time consumption and labor intensity increase significantly
Solution Approach 1:
The patent replaces manual human reading and analysis of messages with an automated computational system. The system uses n-gram extraction, temporal histogram generation, correlation analysis, and distance measurement algorithms to automatically identify concepts and their synonyms, substituting the mechanical human cognitive process with an automated information processing system that achieves both high speed and accuracy.
2Measurement precision
If synonym identification is performed without systematic analysis, then processing speed is maintained, but synonym accuracy decreases
Solution Approach 1:
The patent segments the synonym identification process into distinct analytical components: n-gram extraction from messages, temporal histogram generation to capture usage patterns, correlation analysis to measure relationship strength, and distance measurement to assess lexical similarity. This segmentation allows each component to be optimized independently while working together to achieve accurate synonym identification.
Solution Approach 2:
The system incorporates feedback mechanisms where the results from correlation analysis and distance measurement are used to iteratively refine synonym identification. The temporal histograms provide feedback on usage patterns, and the correlation coefficients feedback on relationship strength, allowing the system to adjust and improve its synonym determinations through multiple analytical passes.
Data Source
AI summary
A technique includes obtaining a plurality of n-grams from a plurality of messages, determining a temporal histogram for each n-gram, and determining synonyms among the n-grams based on a combination of a correlation of the histograms and a distance measure between n-grams.