Context-Based Text Search Disambiguation via Ordered Context Sets
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing text searching tools fail to distinguish between different contextual meanings of a search term and do not return semantically similar terms, leading to irrelevant search results.
Innovation Solution
A context-based text searching method that analyzes documents to determine contextual meanings of search terms, presents an ordered set of contexts for user selection, and highlights semantically similar terms based on user context and training data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional text searching is used to find all instances of a search term, then the search process is simple and fast, but the search results include irrelevant contextual meanings and lack precision
Solution Approach 1:
The patent segments the search process into distinct phases: initial search term matching, context analysis phase, and result filtering phase. The system divides search results into different contextual categories and allows users to select specific contexts, thereby segmenting the monolithic search process into manageable stages that improve precision without overwhelming complexity
Solution Approach 2:
The patent introduces context analysis as an intermediary layer between the search term and the results. This intermediary analyzes the contextual meaning of each match and categorizes results by context type, acting as a mediator that filters out irrelevant results while maintaining the simplicity of the original search interface
2Measurement precision
If context analysis is performed on all search results, then search result precision is improved, but the processing time and computational resources increase
Solution Approach 1:
The patent applies partial context analysis by focusing computational resources on analyzing only the most relevant or ambiguous contexts rather than performing exhaustive analysis on all search results. The system identifies contexts that require disambiguation and applies analysis selectively, reducing overall processing time while maintaining contextual accuracy for critical results
Solution Approach 2:
The patent performs preliminary context analysis by pre-processing and categorizing search results into contextual groups before presenting them to users. This preliminary organization allows for faster retrieval and filtering of context-specific results, reducing the time users spend waiting for processed results
3Measurement precision
If multiple contextual meanings are presented to the user for selection, then search precision is improved, but the user interface complexity increases
Solution Approach 1:
The patent applies local quality by providing context-specific information and options only where needed in the user interface. Rather than overwhelming users with comprehensive context analysis options throughout the entire interface, the system presents contextual disambiguation options locally at the point of search result display, maintaining overall interface simplicity while improving precision where it matters
Data Source
AI summary
A request is received from a user to search a document for at least one search term. The document is analyzed to determine contextual meanings associated with the at least one search term. An ordered set of contexts of the at least one search term is constructed. An option of disambiguation is then prompted to the user to select a context of the ordered set of contexts. Search results are presented to the user associated with the selected context of the at least one search term.