Reverse Geocoding Using POI Feature Scoring
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Solution Overview
Problem
Reverse geocoding systems often provide insufficient information when translating coordinates into a human-readable format, as they rely solely on physical addresses, which may not be useful in unfamiliar areas or situations requiring specific location identification, such as ride-sharing services.
Innovation Solution
A system utilizing points of interest (POIs) to generate candidate places within a predetermined distance from given geographic coordinates, extracting features, and calculating a place score to determine the best candidate location for accurate and useful information delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If reverse geocoding systems provide only physical addresses, then the system complexity is low, but the information usefulness is insufficient for unfamiliar areas or specific location identification
Solution Approach 1:
The patent segments the reverse geocoding process into multiple independent modules: POI data extraction module, feature extraction module, place score calculation module, and candidate place ranking module. Each module handles a specific aspect of the reverse geocoding task, allowing the system to provide comprehensive location information (addresses, POI names, relative positions) while maintaining manageable system complexity through modular design.
Solution Approach 2:
The patent adds a new dimension to reverse geocoding by incorporating POI-based location descriptors alongside traditional physical addresses. Instead of providing only one-dimensional address information, the system now provides multi-dimensional location information including POI names, relative positions, and contextual descriptors, enabling users to identify locations through multiple reference frameworks simultaneously.
2Measurement precision
If the system generates multiple candidate places with feature extraction and scoring, then the location identification accuracy improves, but the processing time increases
Solution Approach 1:
The patent performs preliminary actions by pre-extracting and storing POI data, features, and place scores in advance for multiple candidate places. The system prepares candidate place information including POI names, relative positions, and contextual features before the final selection is made, allowing for rapid retrieval and comparison during the actual reverse geocoding operation, thus maintaining high accuracy while reducing processing time.
Solution Approach 2:
The patent dynamically adjusts parameters such as the search radius, number of candidate places generated, and feature extraction depth based on the specific query context and user needs. By changing these parameters adaptively, the system can balance between generating sufficiently accurate results and minimizing processing time, avoiding unnecessary computation when high precision is not required.
3Ease of operation
If the system provides detailed location information including POI names and relative positions, then the user experience improves, but the data processing complexity increases
Solution Approach 1:
The patent extracts only the essential and most useful features from POI data, such as POI names, relative positions, and key contextual descriptors, rather than processing and presenting all available POI attributes. This selective extraction approach provides users with sufficient location identification information while avoiding the complexity of processing and managing complete POI datasets, thus improving user experience without proportionally increasing data processing complexity.
4Reliability
If the system calculates place scores for multiple candidate places, then the reverse geocoding accuracy improves, but the computational resources required increase
Solution Approach 1:
The patent implements partial action by calculating place scores for a limited number of top candidate places rather than all possible candidates within the search area. The system generates a ranked list of candidate places and computes detailed place scores only for the most promising candidates (e.g., top 5-10 candidates), which is sufficient to achieve high reverse geocoding accuracy while significantly reducing computational resource requirements compared to scoring all potential candidates.
Data Source
AI summary
Systems and methods are provided for receiving geographic coordinates for a location, generating a plurality of candidate places located within a predetermined distance from the location based on the geographic coordinates of the location, and extracting a plurality of features from each candidate place of the plurality of candidate places. The systems and methods are further provided for generating a place score for each candidate place of the plurality of candidate places using the plurality of features for each candidate place of the plurality of candidate places, determining the best candidate place based on the place score for each candidate place of the plurality of candidate places, and providing a place name associated with the best candidate place.