Dynamic Map Display Biasing for Tourist Context
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Solution Overview
Problem
Traditional mapping systems generate identical maps for both locals and tourists, failing to provide tailored information based on user familiarity with the area, leading to irrelevant or less relevant points of interest being displayed.
Innovation Solution
A computer-implemented method that assigns a bias value to points of interest (POIs) based on user classification, modifying their display on a digital map by calculating a rank and adjusting the zoom level according to user interaction data and profile information, ensuring that relevant POIs are prioritized and displayed prominently for tourists or locals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If identical maps are generated for every user, then the mapping system is simple to operate, but the relevance of displayed points of interest deteriorates for tourists
Solution Approach 1:
The patent applies local quality by differentiating the map display based on user location and classification. Tourists viewing maps from outside an area receive customized maps highlighting tourist attractions, while locals viewing maps from within the area receive standard maps. This localized differentiation ensures that each user receives map information tailored to their specific context and needs, resolving the contradiction between simplicity and relevance.
Solution Approach 2:
The patent implements dynamics by making the map generation process adaptive rather than static. The system dynamically determines user classification based on location data and device information, then dynamically adjusts the map content accordingly. This dynamic adaptation allows the system to automatically provide relevant information without requiring manual configuration, maintaining ease of operation while improving information relevance.
2Loss of information
If user classification and bias values are calculated for each POI, then the relevance of displayed points of interest improves, but the device complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating bias values for different POI categories based on historical data and user behavior patterns. These bias values are stored in advance and retrieved during map generation, eliminating the need for real-time complex calculations. This pre-processing approach reduces the computational burden during actual map display while maintaining high relevance of displayed information.
Solution Approach 2:
The system implements self-service by automatically determining user classification and applying appropriate bias values without requiring manual input or configuration. The system uses location data and device information to autonomously identify whether a user is a tourist or local, then automatically adjusts the map accordingly. This automation reduces the operational complexity for users while maintaining sophisticated relevance customization.
Data Source
AI summary
A computer-implemented method and system may modify categories for points of interest (POIs) for display on a map at a client computing device based on a bias value corresponding to a classification of a user. A system may receive interaction events from client computing devices. The interaction events may each include an indication of a user interaction with a POI displayed on a digital map at a client computing device and each POI may include a category and a default zoom level. Using a user's location data, the system and method may classify the user based on the user's familiarity with an area surrounding the interaction event POI and assign a numerical bias to POIs that include the category of each interaction event POI. Subsequent requests for mapping data may then return categories of POIs according to the type of user sending the request based on the bias value.