Natural Language Search Negation Processing
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Solution Overview
Problem
Existing natural language search engines fail to correctly interpret and process negation terms in search queries, leading to incorrect results.
Innovation Solution
The system identifies and processes negation terms in natural language search queries by parsing the query into portions, determining the negation portions, and generating a content query with appropriate negation parameters to exclude specified content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing natural language search engines process queries using simple keyword matching, then the system complexity remains low, but the accuracy of interpreting negation terms deteriorates
Solution Approach 1:
The patent segments the natural language query into distinct portions using a parser, identifying negation portions separately from other query elements. This segmentation allows the system to apply specific negation processing logic to the identified portions while maintaining overall system structure, thereby improving negation interpretation accuracy without proportionally increasing system complexity
Solution Approach 2:
The patent introduces an intermediary component (the negation processing module that works with the parser) that specifically handles negation terms. This intermediary layer processes negation portions between the initial query parsing and the final search execution, improving accuracy by dedicating specific processing logic to negation terms without requiring complete system redesign
2Measurement precision
If the system parses the natural language query to identify negation portions, then the accuracy of search results improves, but the processing time increases
Solution Approach 1:
The system performs preliminary parsing of the natural language query to identify negation portions before executing the full search. By pre-identifying and tagging negation terms and their targets during the query analysis phase, the system prepares the search parameters in advance, which improves final search accuracy while minimizing additional processing time during actual search execution
3Measurement precision
If the system uses advanced parsing algorithms like neural networks to process negation, then the interpretation accuracy improves, but the computational resources required increase
Solution Approach 1:
The patent applies advanced parsing algorithms specifically to the portions of the query that contain negation terms, rather than processing the entire query with high-computational methods. This localized application of sophisticated algorithms to only the necessary segments (negation portions and their targets) improves interpretation accuracy while reducing overall computational resource consumption compared to applying advanced algorithms to the complete query
Data Source
AI summary
Systems and methods are described herein for processing negation in a natural language search query. The natural language search query is parsed to identify a plurality of portions of the natural language search query, and a first portion is determined to be a negation portion. A second portion to which the negation portion applies and a third portion to which the negation portion does not apply are then identified, and a content query is generated which includes a negation parameter corresponding to the second portion, and at least one other parameter corresponding to at least the third portion. Search results of the content query are then generated for output to the user.