Language Processing Apparatus Context-Aware Word Association
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Solution Overview
Problem
The Gale-Shapley algorithm for associating words in text data does not adequately consider context and usage, leading to difficulties in appropriate association.
Innovation Solution
A computer-implemented method that calculates the degree of easiness of association between words and word groups, using a word vector database to determine context association degrees and update word association degrees based on context information, allowing for more accurate word associations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If the Gale-Shapley algorithm is used to associate words based on predetermined degrees of easiness of association, then the association process can be automated, but the context and usage of words are not taken into consideration, leading to inappropriate associations in some cases
Solution Approach 1:
The system pre-calculates and stores the degree of easiness of association between all possible word combinations in a database before actual text processing. This preliminary computation enables the automated Gale-Shapley algorithm to efficiently retrieve and use these pre-computed values during word association, maintaining automation while improving accuracy through context-aware pre-calculated metrics
Solution Approach 2:
The system uses the results of word associations to update and refine the degree of easiness of association values. By analyzing actual association outcomes and their quality, the system feeds back information to adjust the pre-computed values, thereby improving future association accuracy while maintaining the automated process
2Speed
If the degree of easiness of association between words is previously determined using the Gale-Shapley algorithm, then the processing speed is improved, but the context and usage of words are not taken into consideration
Solution Approach 1:
The system performs preliminary computation of association degrees for all word combinations and stores them in a database. This pre-computation captures contextual relationships in advance, enabling fast retrieval during actual processing while maintaining context awareness through the pre-analyzed word relationships
Solution Approach 2:
The system dynamically adjusts the degree of easiness of association parameters based on the specific context of the text being processed. By changing these parameters according to contextual requirements, the system maintains both processing speed through parameterized computation and adaptability to different contextual situations
Data Source
AI summary
A computer-implemented method of processing language, includes: calculating a value indicating a degree of easiness of association between words with regard to one or more combinations of words in a first word group included in first text data and a second word group included in second text data; associating a first word and a second word based on the value indicating the degree of easiness of association; calculating a value indicating a degree of easiness of association between word groups with regard to a word group in the first text data including the first word and a word group in the second text data including the second word, using a result of the associating and the value indicating the degree of easiness of association between the words; and updating the value indicating the degree of easiness of association between the words by using the value indicating the degree of easiness of association between the word groups.