Map Labeling System Using Content Ranking for Clutter Reduction
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Solution Overview
Problem
Current software-based maps face issues with overcrowding due to the addition of extra icons and text, which interferes with basic information and results in an unorganized display, especially when trying to incorporate content like weather or photos.
Innovation Solution
A system and method for custom labeling maps by identifying orientation points based on ranking criteria such as population and popularity, associating content with these points, and re-ranking them for optimal display, ensuring a balanced and organized map layout across different zoom levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If additional icons and text are added to the map to display content like weather or photos, then the information completeness is improved, but the map display becomes overcrowded and basic information becomes difficult to read
Solution Approach 1:
The patent segments the map display into multiple hierarchical levels (default locations vs. custom content locations). Basic map elements maintain their default positions while custom content is placed at alternative locations determined by machine learning models, allowing both basic information and additional content to coexist without overcrowding
Solution Approach 2:
The patent applies local quality by allowing different regions of the map to have different display characteristics. The machine learning model determines optimal display locations for different types of content based on their specific properties and the local context of the map area, ensuring that content is displayed in the most appropriate locations without interfering with basic map readability
2Adaptability or versatility
If custom content is added to the map, then the customization capability is improved, but the display organization deteriorates
Solution Approach 1:
The patent employs preliminary action by using machine learning models to pre-determine the optimal display locations for custom content before the user views the map. The system analyzes content properties, user preferences, and map context in advance to establish an organized display layout, eliminating the need for manual organization and ensuring consistent, well-structured content placement
Solution Approach 2:
The patent implements feedback mechanisms where the machine learning model continuously learns from user interactions and adjusts content display locations accordingly. The system monitors whether content placements are effective and uses this feedback to refine its positioning algorithms, maintaining display organization while adapting to user preferences over time
Data Source
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AI summary
A system and method for generating a content based, custom labeled map is provided. A request for a map is received. The request includes a geographical area to be displayed in the map and a type of content item to be displayed in the map. A plurality of orientation points to display on the map is determined based on a ranking of locations in the geographical area, and one or more pieces of content to be associated with each orientation point is determined. Each orientation point is ranked based in part on ranks of the one or more pieces of content associated with each orientation point. A map is generated to display at the locations of the plurality of orientation points the pieces of content associated with each orientation point at a level of prominence that is based on the ranking of each orientation point.