Facet-Based Query Refinement via Multiple Interpretations
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Solution Overview
Problem
Existing facet-based query refinement methods are limited in generating diverse query interpretations and presenting nuanced facet value representations, leading to suboptimal document set refinement and knowledge discovery.
Innovation Solution
A computer-implemented method that generates multiple query interpretations from an initial query, executes these interpretations to obtain document sets, identifies facet values, and presents a query refinement interface showing facet value representations across different interpretations, allowing users to refine queries based on facet values and their relative importance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple query interpretations are generated and executed, then query refinement accuracy is improved, but system complexity and processing time increase
Solution Approach 1:
The patent segments the query processing into multiple independent query interpretations, where each interpretation represents a different way of understanding the user's query intent. By dividing the monolithic query processing into separate interpretation paths, the system can explore multiple semantic meanings simultaneously without overwhelming complexity in a single processing pipeline.
Solution Approach 2:
The patent adds a dimensional aspect to query processing by introducing multiple interpretation dimensions. Instead of processing queries in a single linear fashion, the system creates parallel processing dimensions where each query interpretation represents a different semantic dimension, allowing comprehensive analysis from multiple angles.
2Measurement precision
If multiple query interpretations are generated and executed, then query refinement accuracy is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary actions by pre-generating multiple query interpretations before executing the actual search. This allows the system to prepare various semantic interpretations in advance, so when the search needs to be refined, the interpretations are already available, reducing the time penalty of multiple processing paths.
Solution Approach 2:
The system implements self-service mechanisms where the query interpretation process automatically generates and evaluates multiple interpretations without requiring external intervention. The system serves itself by autonomously managing the multiple interpretation paths, selecting relevant ones, and integrating results, which optimizes processing time through automated decision-making.
3Loss of information
If facet value representations are presented across different query interpretations, then user understanding is improved, but interface complexity increases
Solution Approach 1:
The patent merges facet value representations from multiple query interpretations into a unified presentation. Instead of showing separate facet lists for each interpretation, the system combines and consolidates the facet information, presenting a integrated view that maintains user understanding while reducing interface complexity through consolidation.
Solution Approach 2:
The patent creates a universal facet presentation interface that serves multiple query interpretations simultaneously. The facet value representation system is designed to be multi-functional, accommodating different interpretation types and formats while maintaining a consistent user experience, thereby improving understanding without proportionally increasing interface complexity.
Data Source
AI summary
Facet-based query refinement based on multiple query interpretations is provider through a process that includes receiving a query for querying documents, of a whole document set, that deviate by one or more facet values. The process generates different query interpretations from query text of the query. The process executes the different query interpretations to obtain resulting document sets. For each different query interpretation, the executing executes the query interpretation to obtain a resulting document set corresponding to that query interpretation, and identifies facet values represented in the resulting document set. The process builds and presents to a user a query refinement interface, presenting the different query interpretations and properties of the resulting document sets, as well as, for each of the one or more facet values, and relative to each other, facet value representation of the facet value in each of the resulting document sets.