Dynamic Search Result Formatting Based on User Interaction
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Solution Overview
Problem
Current search systems fail to adapt search results dynamically based on user interactions, leading to suboptimal presentation and user experience, as they do not effectively track and respond to user mindset shifts during the search process.
Innovation Solution
A system that receives and processes user interactions to adapt search results by transitioning through different formatting levels, based on user interactions such as page-downs and swipes, to better match the user's mindset, and also utilizes saved search properties to refine search results and reorder data item information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If search results are presented in a static format, then the system structure is simple, but the user experience and relevance are suboptimal
Solution Approach 1:
The patent implements dynamic formatting levels that automatically adjust based on user interactions. The system transitions from static to dynamic presentation by monitoring user behavior (scrolling, clicking, time spent) and adapting the search results format accordingly, resolving the contradiction between adaptability and complexity through automated dynamic adjustment
Solution Approach 2:
The system incorporates feedback loops where user interactions with search results are tracked and fed back into the formatting level determination. This feedback mechanism allows the system to learn from user behavior and continuously optimize the presentation format, achieving adaptability while managing complexity through systematic feedback processing
2Ease of operation
If the system tracks detailed user interactions, then user experience improves, but data processing complexity increases
Solution Approach 1:
The patent segments user interactions into distinct types (scrolling, clicking, hovering, time spent) and processes each type through specific tracking mechanisms. By dividing the complex task of user behavior analysis into manageable segments, the system improves user experience while controlling data processing complexity through structured segmentation
Solution Approach 2:
The system implements partial tracking by focusing on the most significant user interactions rather than every possible action. It monitors key behaviors that most impact search result relevance while ignoring minor interactions, achieving improved user experience with reduced data processing complexity through selective partial action
3Measurement precision
If search results are dynamically adjusted, then relevance to user intent improves, but response time may increase
Solution Approach 1:
The system performs preliminary actions by pre-determining formatting levels and preparing adaptive templates in advance. When user interactions are detected, the system can quickly apply pre-prepared formatting adjustments rather than generating new formats from scratch, improving relevance while minimizing response time through preliminary preparation
Solution Approach 2:
The patent implements parameter changes by adjusting discrete formatting parameters (layout, density, information hierarchy) based on detected user intent. The system changes specific presentation parameters rather than completely regenerating search results, achieving improved relevance with faster response times through targeted parameter adjustment
Data Source
AI summary
Methods and systems to adapt search results are described. The system receives search information that includes a constraint over a network. The system generates a first search result based on the search information. The system communicates a first user interface, over the network, to the client device. The first user interface is formatted based on first formatting level information. The system receives a first request, over the network, from the client device. The first request includes a description of a first interaction with the first search result. The system identifies a first formatting level based on at least one interaction that was received previous to receiving the first request. The system transitions to a second formatting level based on the first formatting level and the first interaction. The second formatting level is associated with second formatting level information.