Map POI Scoring for Clearer Ride Pickup Locations
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems struggle to effectively communicate real-life geography to users, particularly in locations lacking prominent landmarks, making it difficult for users to identify meeting points during travel coordination services.
Innovation Solution
An online system enhances map displays by identifying and scoring points of interest near a user's location, incorporating building boundaries, exits, and relevant hotspots, and adjusting the display based on visibility and trip frequency to improve navigation and coordination between riders and providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If map data is enhanced with detailed points of interest information, then map quality and user experience are improved, but data processing time and computational resources increase
Solution Approach 1:
The system pre-generates and stores structured point of interest data including categories, keywords, and hierarchical relationships before they are needed for map display. This preliminary structuring of data allows for rapid retrieval and enhancement of map data without requiring intensive processing during actual map rendering, thus improving map quality while minimizing processing time delays
2Loss of information
If comprehensive points of interest data is collected and stored, then map information completeness is improved, but data storage requirements and system complexity increase
Solution Approach 1:
The point of interest data is segmented into hierarchical categories (e.g., food, shopping, entertainment) with sub-categories and structured metadata. This segmentation allows the system to store comprehensive information in an organized manner, enabling selective retrieval based on user needs without requiring the entire dataset to be processed simultaneously, thus maintaining information completeness while managing system complexity
Solution Approach 2:
The system transforms unstructured point of interest information into structured data with standardized parameters including categories, keywords, coordinates, and operational hours. This parameter-based structuring enables efficient storage, retrieval, and filtering of comprehensive POI data without proportionally increasing system complexity, as the structured format allows for optimized database queries and selective data loading
Data Source
Figure 1
Figure 2
Figure 3A
AI summary
An online system receives a trip request including a location of the user requesting the trip. The online system identifies buildings or geographies based on the received location and determines location boundaries associated with the identified buildings or geographies. The online system identifies a set of hotspots representing locations that are frequently used for pickup or drop off. The online system additionally identifies a set of points of interest. The points of interest are, for example, businesses, landmarks, building names, or other visible information related to the location. The online system scores the set of points of interest based on a relative value of displaying the point of interest for orientation or navigation purposes. The online system modifies a user interface to display a map of the area including the identified location boundaries, hotspots, and one or more points of interest based on the scoring.