Search Engine Suggestion System for Query Refinement
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Solution Overview
Problem
Users often become frustrated with search engines when their informational needs are not met, as existing search engines may not provide relevant resources, requiring frequent query refinement and leading to dissatisfaction.
Innovation Solution
A user device suggests alternative search engines by detecting unsatisfied informational needs through user interactions, offering the same or modified search queries to improve search results, allowing users to compare results from different engines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a user periodically refines the search query to improve relevance, then the precision of search results improves, but the time required for the search process increases
Solution Approach 1:
The system performs preliminary actions by proactively generating and presenting alternative search queries before the user has to manually refine their query multiple times. The automated assistant analyzes the current search results, identifies potential improvements, and prepares refined query options in advance, allowing the user to quickly select from pre-prepared alternatives rather than iteratively refining queries themselves.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring user interactions with search results (such as selections, clicks, or lack thereof) and using this feedback to automatically generate improved search queries. The system learns from user behavior patterns and adjusts subsequent query suggestions accordingly, creating a closed-loop system that progressively improves result precision based on actual user needs.
2Quantity of substance
If the search engine identifies more resources to increase recall, then the quantity of search results increases, but the precision of relevant results decreases
Solution Approach 1:
The system changes parameters by dynamically adjusting search query characteristics based on analysis of initial results and user behavior. Instead of simply increasing the number of results through broader queries, the automated assistant modifies query parameters (such as adding specific filters, changing terminology, or adjusting scope) to optimize the balance between result quantity and relevance precision.
3Ease of operation
If the user becomes frustrated with the search engine due to unsatisfied informational needs, then the user experience deteriorates, but the system complexity increases when implementing suggestions for alternative search engines
Solution Approach 1:
The system applies self-service by enabling the automated assistant to independently analyze search result quality, detect user frustration signals, generate alternative queries, and present improved options without requiring complex manual intervention or configuration. The system serves itself by autonomously monitoring its own performance and initiating corrective actions when results are unsatisfactory.
Data Source
AI summary
Methods, computer-readable media, and systems for suggesting a search engine to search for resources. Multiple search results determined by a first search engine as satisfying multiple first search queries are received and displayed in a user interface. That the search results received from the first engine do not satisfy an informational need of a user that input the search queries is determined. In response, a suggestion to provide a similar search query to a second search engine is displayed in the user interface.