Navigation Route Planning via Media Density Scoring
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Solution Overview
Problem
Conventional navigation applications fail to display all points of interest (POIs) along a route, as they are limited to predefined categories and do not account for popularity, leading to users being unaware of additional relevant POIs and lacking distinction between them based on popularity.
Innovation Solution
A navigation system that determines a route from an origin to a destination and recommends locations of interest with a media density score greater than a threshold, within a specified range of deviation from the route, using media files from various sources like social networks and websites to calculate scores based on importance and number of recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional navigation applications display only POIs adjacent to the route in predefined categories, then the device complexity and information processing load are reduced, but the quantity of useful information and user awareness of relevant POIs decrease
Solution Approach 1:
The system pre-calculates media density scores for all POIs along the route before navigation begins. This preliminary computation allows the system to have all POI popularity data ready in advance, enabling comprehensive POI display without increasing real-time processing complexity during navigation.
Solution Approach 2:
The system uses media files (photos, videos, reviews) from social networks and websites as proxies for POI popularity and quality. Instead of directly measuring POI attractiveness, it copies and analyzes existing user-generated content about locations, providing rich information without direct measurement complexity.
2Measurement precision
If the navigation system incorporates media density scoring based on multiple media files, then the measurement precision of POI popularity is improved, but the loss of time for data processing increases
Solution Approach 1:
Media density scores are calculated and stored in advance for all potential POIs along possible routes. This pre-computation eliminates the need for real-time analysis of media files during navigation, reducing processing time while maintaining precise popularity measurements.
Solution Approach 2:
The system calculates media density scores for all POIs within a certain distance of the route, even though not all will be displayed. This excessive computation is performed in advance, allowing the system to quickly filter and display only the most relevant POIs during navigation without time constraints.
3Quantity of substance
If the system displays all POIs within a range of deviation from the route, then the quantity of substance (number of POIs) increases, but the ease of operation and user decision-making deteriorate
Solution Approach 1:
The system applies different display priorities to different POIs based on their media density scores. High-scoring POIs are prominently displayed with more information, while lower-scoring POIs are displayed with less prominence. This differentiated approach provides comprehensive information while guiding user attention to the most interesting locations.
Solution Approach 2:
The system changes the display parameter from binary (display/not display) to graded (display priority levels) based on media density scores. This allows the system to present all POIs within deviation range while organizing them by popularity, making it easier for users to identify and select interesting locations.
Data Source
AI summary
The disclosure is directed to routing to a destination. An aspect determines a route from an origin to the destination, and recommends a location of interest. The location of interest is a location with a media density score is greater than a threshold and within a range of deviation from the route. The media density score is based on a number of recommendations of a media file related to the media density score.