Graph Matching for Query Ambiguity Reduction
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Solution Overview
Problem
Conventional natural language understanding techniques face difficulties in interpreting natural language queries due to ambiguity in word meanings, leading to inaccurate responses.
Innovation Solution
A computer-implemented method and system that determine potential meanings of words in a query, generate a matching graph with similarity scores, and reduce ambiguity by assigning meanings to words or phrases using key words, similarity scores, and analyzing word order, with the option to present clarification questions to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional natural language understanding techniques are used to interpret queries, then the system can process natural language inputs, but the interpretation accuracy deteriorates due to word ambiguity
Solution Approach 1:
The patent introduces an intermediary component (the ambiguity resolution module with matching graph) that mediates between the ambiguous natural language input and the required precise interpretation. This intermediary analyzes multiple potential meanings, scores them based on context, and selects the most appropriate interpretation, thereby resolving the contradiction between processing natural language and achieving accurate interpretation.
Solution Approach 2:
The system changes the parameter of word meaning representation from a single fixed meaning to multiple potential meanings with associated confidence scores. By representing meanings as a distribution across multiple possibilities rather than a single value, the system can capture ambiguity while still proceeding with interpretation using the most likely meanings.
2Reliability
If multiple potential meanings are considered for each word, then the system can capture word ambiguity, but the computational complexity increases due to generating and analyzing matching graphs
Solution Approach 1:
The system applies partial action by not considering all possible meanings equally, but rather focusing on the most relevant potential meanings based on context and scoring. The matching graph processes only the necessary subset of meaning combinations required to resolve ambiguity, rather than exhaustively evaluating all possible interpretations.
Solution Approach 2:
The system performs preliminary action by pre-scoring and ranking potential meanings before full interpretation. The matching graph is constructed and analyzed in advance to identify the most likely word meanings, allowing the system to resolve ambiguity efficiently before generating the final query interpretation.
3Measurement precision
If the system requests clarification from users when ambiguity cannot be resolved, then the interpretation accuracy improves, but the response time increases due to additional user interaction
Solution Approach 1:
The system implements feedback by monitoring the confidence levels of its interpretation and selectively seeking user clarification only when necessary. The matching graph analysis provides feedback on interpretation certainty, and the system uses this feedback to determine whether to proceed with the current interpretation or request clarification, thereby balancing accuracy with response time.
Data Source
AI summary
Embodiments of the present invention provide systems, methods, and computer storage media directed at interpreting a query related to a dataset to reduce ambiguity of the query. In embodiments, a method includes determining potential meanings of words of a natural language query related to a particular dataset. A matching graph can be generated for the words of the query and the potential meanings for the words including similarity scores for the potential meanings. The method further includes reducing ambiguity of the matching graph by assigning selected potential meanings to the words. Upon reducing ambiguity of the matching graph, the matching graph can be used to provide a response to the query. Other embodiments may be described and/or claimed herein.