Federated Search Query Ranking via User Feedback Index
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Solution Overview
Problem
Traditional search systems fail to incorporate user feedback effectively into their search indices, leading to suboptimal query result rankings and relevance, as they do not capture user interactions with search results to adjust future query outcomes.
Innovation Solution
A method and apparatus that perform multi-domain query searches by receiving user feedback during search sessions, generating a feedback index that ranks query results based on user engagement and abandonment events, and using this feedback to update a results cache for improved query result relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional search systems use static search indices without user feedback, then the system structure remains simple, but the relevance of search results deteriorates
Solution Approach 1:
The patent implements feedback loops where user interactions (clicks, dwell time, queries) are captured and fed back into the search system. This feedback is processed to update the search index and improve result relevance dynamically, resolving the contradiction between maintaining simple structure and improving reliability.
Solution Approach 2:
The search index is transformed from a static structure to a dynamic one that continuously adapts based on user feedback. The system dynamically updates the index with new information from user interactions, allowing it to maintain high relevance while managing complexity through automated processes.
2Reliability
If user feedback is captured and processed in real-time, then search result relevance improves, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary processing of user feedback by maintaining queues and buffers that pre-process interaction data before it needs to be incorporated into the search index. This reduces the time pressure during actual query processing while still achieving real-time relevance improvements.
Solution Approach 2:
The feedback processing operates continuously in the background rather than interrupting query processing. User interactions are captured and processed in a continuous stream, allowing the system to maintain high query accuracy without adding noticeable delay to user operations.
3Adaptability or versatility
If the search index is updated frequently with user feedback, then the personalization and relevance improve, but the system complexity and resource consumption increase
Solution Approach 1:
The search index is segmented into different components that can be updated independently based on feedback types. Rather than updating the entire index simultaneously, the system divides it into manageable segments that can be processed and updated separately, reducing overall complexity while maintaining adaptability.
Data Source
AI summary
A method and apparatus that generates a plurality of ranked query results from a query over a plurality of separate search domains. In this embodiment, the device receives the query and determines a plurality of results across the plurality of separate search domains using the query. The device further characterizes the query. In addition, the device ranks the plurality of results based on a score calculated for each of the plurality of results determined by a corresponding search domain and the query characterization, where the query characterization indicates a query type.