Location Information Sorting by Geographic Segmentation
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Solution Overview
Problem
Existing systems for presenting location-dependent information to users fail to effectively sort and prioritize results based on multiple criteria beyond distance, leading to suboptimal relevance and user experience.
Innovation Solution
A system and method that select multiple geographic areas around a location of interest, sort listings within each area based on criteria such as distance, user ratings, and advertisement fees, and concatenate results to provide a comprehensive, localized, and relevant presentation of location-dependent information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the entire list of service providers is sorted based on distance from the location of interest, then the sorting is simple and fast, but the relevance and user experience are suboptimal because it ignores other important criteria such as user ratings and advertisement fees
Solution Approach 1:
The patent divides the list of service providers into multiple geographic subsets based on predefined geographic areas (e.g., neighborhoods, districts). Each subset is then sorted independently using different criteria, allowing the system to maintain simplicity within local groups while achieving comprehensive sorting across the entire list. This segmentation enables parallel processing and reduces computational complexity.
Solution Approach 2:
The patent applies different sorting criteria to different geographic areas. Within each geographic subset, the system can prioritize different factors such as distance, user ratings, or advertisement fees based on local preferences or characteristics. This allows the system to optimize relevance for each local area while maintaining overall efficiency.
2Reliability
If only one subset of service providers within a certain geographic area is selected and sorted, then the presentation is localized and relevant, but the comprehensive coverage of all service providers is reduced
Solution Approach 1:
The patent partitions the complete list of service providers into multiple geographic subsets based on predefined areas. Each subset represents a specific geographic region and is sorted independently. By presenting multiple sorted subsets rather than a single sorted list, the system maintains local relevance for each area while ensuring comprehensive coverage of all service providers across the entire database.
Solution Approach 2:
The patent introduces a geographic dimension to the sorting process by organizing service providers into spatially-based subsets. This dimensional approach allows the system to present results in a hierarchical manner: first grouped by geographic area, then sorted within each group. This enables users to explore results at different geographic levels while maintaining comprehensive coverage.
3Reliability
If service providers are sorted based on multiple criteria such as distance, user ratings, and advertisement fees, then the relevance and user experience are improved, but the sorting complexity and processing time increase
Solution Approach 1:
The patent divides the sorting task into multiple independent stages: first grouping service providers by geographic area, then sorting each group by different criteria. This segmentation allows the system to apply complex multi-criteria sorting only to smaller subsets rather than the entire list, reducing overall computational complexity while maintaining high relevance.
Solution Approach 2:
The patent applies different sorting criteria to different geographic subsets based on local characteristics and user preferences. This allows the system to optimize for relevance within each local area using appropriate criteria, while avoiding the need to apply complex multi-criteria sorting to the entire national or global list, thereby reducing overall processing complexity.
Data Source
AI summary
Systems and methods sort location dependent information based on selecting multiple groups of information according to location, ordering the groups based on location, and ordering the information within the groups based on at least one or more other criteria. The size(s) of the areas used to select the groups may be predetermined, or dynamically determined (e.g., based on clustering of information along distance to a location of interest).