Adaptive Search Vector Shifting for Dynamic Query Refinement
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Solution Overview
Problem
Existing search engines are inefficient as they do not dynamically adjust search results based on user interactions, requiring users to manually rewrite search queries to refine their searches, leading to an inefficient searching process.
Innovation Solution
An adaptive search system that monitors user interactions with search results, dynamically modifying the search query vector in real-time to adjust search results by shifting away from rejected documents and towards accepted ones, without requiring users to manually alter their queries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the search engine displays static search results without dynamic adjustment, then the system complexity is low, but the search efficiency and user satisfaction deteriorate
Solution Approach 1:
The system implements feedback by monitoring user interactions with search results (clicks, views, time spent) and using this information to dynamically adjust and re-rank search results. The search engine continuously receives feedback from user behavior and modifies subsequent search result presentations without requiring manual query rewriting, thereby improving search efficiency while managing system complexity through automated feedback loops.
Solution Approach 2:
The search engine performs self-service by automatically detecting user preferences through interaction patterns and autonomously adjusting search results. Instead of requiring users to manually refine queries, the system self-corrects and adapts the search results based on observed user behavior, improving efficiency while keeping the interface simple for users.
2Measurement precision
If the user manually rewrites search queries to refine searches, then the search precision can be improved, but the time consumption and operational complexity increase
Solution Approach 1:
The system uses feedback from user interactions (which documents are clicked, viewed, or ignored) to automatically refine search results. This eliminates the need for users to manually rewrite queries while maintaining or improving search precision, as the system learns from user behavior patterns and adjusts results accordingly, significantly reducing time consumption.
Solution Approach 2:
The system replaces the mechanical process of manual query rewriting with an automated electronic system that detects user interactions and dynamically adjusts search results. This substitution eliminates the need for users to physically type and resubmit queries, reducing time consumption while maintaining search precision through automated analysis of user behavior.
3Adaptability or versatility
If the search engine remains disconnected from the user's searching process, then the device complexity is low, but the adaptability to user needs deteriorates
Solution Approach 1:
The search engine becomes connected to the user's searching process through feedback mechanisms that monitor interactions with search results. This connection enables the system to adapt to user needs by detecting patterns in user behavior and dynamically adjusting subsequent search results, improving adaptability while managing complexity through automated feedback processing rather than complex user interaction management.
Data Source
AI summary
Systems, methods, and other embodiments associated with an adaptive search system are described. In one embodiment, user actions are monitored on a search results list in a graphical user interface, wherein the search results list is obtained based on a query vector representing a search query. The query vector is dynamically modified in response to the user actions on a selected result document by shifting the query vector away from the selected result document in a vector space in response to the user rejecting the selected result document. A revised search results list is then generated without the user changing the search query by executing the modified query vector in a search.