Search Query Calibration via Result Set Association
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Solution Overview
Problem
Current methods for calibrating site-level search results on ecommerce websites often fail to provide relevant results on the first attempt, requiring site administrators to enter multiple search queries to find desired information, which is inefficient and does not ensure seamless user experience.
Innovation Solution
The method involves generating a first result set from a search query, determining if it lacks desired results, generating a second result set from a related search query that includes the desired results, and associating the second result set with the first query for subsequent executions, ensuring relevant results are displayed when the first query is re-entered.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single search query is executed to find desired results, then search efficiency is improved, but the search system cannot adapt to improve result relevance when initial queries fail
Solution Approach 1:
The system performs preliminary actions by executing a second search query when the first query fails to return desired results. The results from this second query are then stored and associated with the first query, so that subsequent executions of the first query benefit from the corrected search strategy established in advance.
Solution Approach 2:
The system implements feedback by analyzing the results of the first search query, determining that desired results are missing, then executing a second query to obtain better results. The association of the second query's results with the first query creates a feedback loop that improves future search outcomes for the same query.
2Reliability
If multiple search queries are entered to find desired information, then result relevance is improved, but user time and operational complexity increase
Solution Approach 1:
The system performs self-service by automatically executing the second search query and associating its results with the first query when the first query fails to return desired results. This eliminates the need for users to manually enter multiple search queries, as the system autonomously corrects its own search failures and caches the corrected results for future use.
Solution Approach 2:
The system performs the corrective search action in advance by executing the second query immediately when the first query fails, rather than waiting for the user to manually try again. The results are then stored and associated with the original query, so subsequent user interactions benefit from this preliminary corrective action without additional time investment.
3Reliability
If multiple search queries are entered to find desired information, then result relevance is improved, but the process becomes less efficient
Solution Approach 1:
The system autonomously manages the multi-query process by automatically detecting when the first query fails to return desired results, executing the second corrective query, and associating the improved results with the original query. This self-service approach maintains high result relevance while preserving search efficiency, as the system handles the complexity of multiple queries without requiring multiple user interactions.
Solution Approach 2:
The system performs the corrective search and result association in advance, so that when users subsequently execute the first query, they immediately receive the improved results from the second query without experiencing the inefficiency of manual multi-query processes. The preliminary action of caching corrected results eliminates the need for repeated corrective searches.
Data Source
AI summary
Approaches presented herein enable calibrating site-level search results by associating a set of search results of a second search query with a first search query for subsequent uses of the first search query. Specifically, a first result set is generated from a first search query. The first result set does not include one or more desired query results. A second result set is generated from a second search query. The second result set includes the one or more desired query results. The second result set is associated with the first search query so as to include the one or more desired query results when the first search query is subsequently executed.