Neuro-symbolic Identigen Processing for Text Disambiguation
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Solution Overview
Problem
Existing computing systems face challenges in efficiently extracting useful information from large volumes of data due to issues like data accuracy and variations in text interpretation across languages and regional dialects.
Innovation Solution
The computing system employs a method that includes generating data representations of data, analyzing the data using these representations, and utilizing AI servers to ingest content, extract knowledge, and interact with user devices to facilitate the issuance of user messages and query responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If pattern recognition techniques and statistical reasoning are used to process text, then text interpretation capability is improved, but handling of ambiguities and language variations remains insufficient
Solution Approach 1:
The patent segments text processing into distinct stages: initial pattern recognition, statistical analysis, and subsequent disambiguation steps. This segmentation allows the system to handle different aspects of text interpretation separately, improving overall reliability by addressing ambiguities in dedicated processing stages rather than attempting to resolve them all at once.
Solution Approach 2:
The patent introduces intermediary processing layers between raw text input and final interpretation. These intermediaries include statistical models and pattern recognition algorithms that bridge the gap between ambiguous text and meaningful interpretation, allowing the system to handle language variations and ambiguities more effectively.
2Ease of operation
If grammar based techniques are used to classify words and form sentences, then grammatical structure is improved, but identification of actual word meanings is lost
Solution Approach 1:
The patent merges grammatical analysis with semantic interpretation by combining grammar-based classification techniques with statistical reasoning and pattern recognition. This merging allows the system to maintain grammatical structure formation capabilities while simultaneously preserving and enhancing word meaning identification through multiple complementary approaches.
Solution Approach 2:
The patent employs a composite approach by integrating multiple processing methodologies (grammar-based techniques, statistical reasoning, pattern recognition) into a unified text processing system. This composite methodology allows the system to leverage the strengths of each individual approach while compensating for their respective weaknesses, particularly in preserving word meaning information.
Data Source
AI summary
A method executed by a computing device includes determining a set of identigens for each widely-known word of a query to produce sets of identigens. A set of identigens of the sets of identigens represents one or more different meanings of a word of the query. The method further includes determining another set of identigens for a remaining word to produce an alternate set of identigens. The method further includes selecting an identigen for each set of identigens to produce a query entigen group. The method further includes matching the query entigen group to a set of response entigens to produce a response entigen group as a query response.