Ambiguous Query Resolution via Historical Session Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional search engines often misinterpret ambiguous search queries, leading to the presentation of undesired search results due to their inability to accurately detect semantically ambiguous or multi-language queries, resulting in user frustration and decreased efficiency in finding relevant items.
Innovation Solution
A system that analyzes historical session data to identify semantically ambiguous and multi-language queries by detecting rapid correction instances and translation-based category sector discrepancies, and generates a query resolution interface displaying categorical groupings to clarify user intentions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional search engines process ambiguous queries using conventional interpretation methods, then the search system operates with simple processing logic, but the search results become irrelevant and fail to meet user needs
Solution Approach 1:
The system performs preliminary analysis of historical session data to identify ambiguous queries before they are processed in real-time searches. By pre-processing and storing ambiguous query patterns, the system prepares resolution strategies in advance, improving interpretation accuracy without adding complexity to real-time search operations.
Solution Approach 2:
The system introduces an intermediary component that acts as a bridge between the ambiguous query and the search results. This intermediary analyzes the query, detects ambiguity, and generates multiple possible interpretations, allowing the system to resolve ambiguity without fundamentally changing the core search engine architecture.
2Reliability
If the search engine presents results based on literal query interpretation, then the search process is fast and efficient, but the results are irrelevant when queries are ambiguous
Solution Approach 1:
The system pre-identifies and stores ambiguous queries from historical data, preparing multiple possible interpretations in advance. When an ambiguous query is detected, the system can immediately present pre-computed result sets, avoiding time-consuming real-time analysis and maintaining fast response times while improving result relevance.
Solution Approach 2:
The system applies partial analysis by focusing only on detecting ambiguity rather than fully resolving it in real-time. By identifying ambiguous queries and presenting multiple possible result sets without completely resolving the ambiguity, the system reduces processing time while still improving result relevance compared to traditional single-interpretation approaches.
3Measurement precision
If the system provides detailed query resolution options to users, then query ambiguity is effectively resolved, but the user interface becomes more complex
Solution Approach 1:
The system segments the query resolution process by separating ambiguity detection from ambiguity resolution. The system automatically detects ambiguous queries and generates multiple result sets, then presents them in a segmented, organized manner that reduces interface complexity while maintaining precise user intent detection through structured presentation options.
Data Source
AI summary
Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and execute functions comprising: storing historical session data pertaining to user sessions and archived search queries submitted by users to a search engine; analyzing the historical session data to identify ambiguous queries, including semantically ambiguous queries and multi-language queries; monitoring search queries submitted to the search engine to detect the ambiguous queries; and in response to detecting an ambiguous query, generating a query resolution interface that displays categorical groupings, each of which corresponds to a possible intention of the ambiguous query. Other embodiments are disclosed herein.