Search Result Association via Query Relationship Mapping
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Solution Overview
Problem
Conventional search systems return the same results for a query until a new data set is indexed, failing to adapt to user behavior and query relationships, which limits the relevance of search results over time.
Innovation Solution
A system that maps search results from a current query to a previously executed query based on detected user behavior, such as shared attributes and temporal relationships, using a machine learning engine to determine query relationships and associate relevant search results across queries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If search results are determined based on a match between query terms and search result terms, then the search system is simple and consistent, but the search results cannot adapt to user behavior and query relationships over time
Solution Approach 1:
The system performs preliminary actions by detecting user behavior patterns and query relationships in advance, storing this information for later use. When a new query is received, the system has already prepared the behavioral data needed to adapt results, allowing dynamic adaptation without complex real-time processing.
Solution Approach 2:
The patent introduces an intermediary mechanism that detects and analyzes the relationship between current queries and prior queries, as well as user behavior patterns. This intermediary layer processes behavioral data and uses it to modify search results, bridging the gap between simple term matching and complex adaptive behavior without requiring the entire system to become overly complex.
2Reliability
If the same search results are returned for a query until new data is indexed, then the system is stable and consistent, but the relevance of search results deteriorates over time
Solution Approach 1:
The system implements feedback by detecting user behavior patterns and query relationships, then using this feedback to dynamically adjust search results. The system continuously monitors how users interact with search results and uses this information to refine future results, maintaining both consistency through structured processing and relevance through adaptive adjustments.
Solution Approach 2:
The patent applies dynamics by making the search result generation process adaptable and changeable based on detected user behavior and query relationships. Rather than static term matching, the system dynamically adjusts which results are returned based on real-time behavioral patterns, ensuring results remain relevant while maintaining systematic consistency through defined adjustment rules.
3Loss of information
If search results are dynamically adjusted based on user behavior, then search result relevance is improved, but the system complexity increases
Solution Approach 1:
The system performs preliminary detection and analysis of user behavior patterns and query relationships before they are needed for result adjustment. By pre-processing and storing behavioral data in an organized manner, the system reduces the complexity of real-time adjustments while maintaining high result relevance through readily available behavioral insights.
Data Source
AI summary
Techniques for associating a selected search result, for a current query, with a recently executed prior query are disclosed. The system receives a first query from a user and presents a first set of search results. The system receives a second query from the user, subsequent to presenting the first set of search results, and presents a second set of search results. The system determines that a user selects a particular search result from the second set of search results. The system determines an association between the first query and the second query. Responsive to determining that the user selected the particular search result and the association between the first query and the second query, the system associates the particular search result with the first query. Subsequently, the system receives a new request for execution of the first query and, in response, presents at least the particular search result.