Dynamic Search Result Interfaces for Contextual Content Formatting
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Solution Overview
Problem
Existing systems struggle to provide relevant and varied content formats for users at different stages of their search process, often occupying valuable space and attention with standard formats that do not cater to individual user needs.
Innovation Solution
A system that selects and presents dynamic user interfaces based on query information, user demographics, and interaction history, allowing for tailored content presentation, including advertisements, through a model that learns from user interactions to improve relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If standard formats are used to present additional content on search pages, then content can be consistently displayed, but valuable space and attention are occupied without catering to individual user needs
Solution Approach 1:
The patent applies dynamics by making the user interface format selectable and changeable based on user preferences and search query characteristics. Instead of a fixed standard format, the system dynamically adjusts the presentation format of additional content (such as product information, images, or descriptions) to match what the user is currently searching for, thereby reducing wasted space while maintaining adaptability.
Solution Approach 2:
The patent implements local quality by allowing different portions of the search results page to have different formats based on relevance and user needs. Rather than applying a uniform format to all additional content, the system selectively formats content locally - for example, displaying images for visual search queries or detailed descriptions for technical product searches - thus optimizing space utilization for each local section.
2Quantity of substance
If a myriad of information is presented in standard format, then comprehensive content is provided, but information relevance to user needs at different search stages is reduced
Solution Approach 1:
The patent applies segmentation by dividing the comprehensive information into distinct segments or categories (such as product details, pricing, images, reviews) and selectively presenting only the relevant segments based on the search query and user stage. This allows the system to provide comprehensive information when needed while filtering out irrelevant information for users at different search stages, thereby maintaining high relevance.
Solution Approach 2:
The patent implements preliminary action by analyzing the search query and user context before presenting additional content, so that the most relevant information is prepared and presented in advance. The system predicts what information the user will need based on the search stage and query type, pre-formating and presenting only that relevant information rather than dumping all available data, thus preventing information loss through irrelevance.
3Stability of the object's composition
If additional content is presented in the same standard web page format, then consistency is maintained, but the ability to provide tailored content formats is limited
Solution Approach 1:
The patent applies universality by creating a multi-functional content delivery system that can handle multiple content formats (text, images, videos, structured data) through a single unified framework. The system maintains consistency in how content is delivered (through standardized API calls and processing pipelines) while simultaneously supporting diverse content formats, allowing the same infrastructure to adapt to different user needs and search contexts without compromising stability.
Data Source
AI summary
A content provider can provide content, such as advertisements or other promotional material, to a recipient. A distribution system of the content provider can receive a query and select one or more advertisements and a user interface for presenting the advertisements based on the query, information associated with the user, a set of queries received from the user, and/or other information. A model for selecting the user interface can be generated by serving available user interfaces randomly or pseudo-randomly and monitoring user interaction with the served user interfaces. The model can be updated during regular use based on the performance of the user interfaces.