Geocoding System Selecting Geocoder by Location Data Type
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Solution Overview
Problem
Current data processing systems lack an efficient method to geo-enrich data by selecting the appropriate geocoder based on the type of location data, which limits the ability to perform spatial operations and utilize geocoded data effectively in applications like mapping and analytics.
Innovation Solution
A system that receives a request to geo-enrich data, selects a geocoder from a plurality of geocoders (internal or external services) based on the location data type, geo-enriches the data, and optionally persists it for later use, allowing for spatial operations and map-based applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single geocoder is used for all location data, then the system is simple to manage, but it cannot efficiently handle different types of location data (e.g., latitude/longitude vs. address data)
Solution Approach 1:
The system segments the geocoding functionality by maintaining multiple geocoders (internal and external services) specialized for different location data types. Each geocoder is selected based on the specific type of location data being processed, allowing the system to handle latitude/longitude pairs, address data, and other location formats efficiently without forcing a one-size-fits-all approach.
Solution Approach 2:
The patent introduces an intermediary component that automatically selects the appropriate geocoder based on the location data type. This mediator analyzes the input data characteristics and routes requests to the most suitable geocoder, shielding users from the complexity of managing multiple geocoders while maintaining high adaptability to different data formats.
2Speed
If geocoding is performed without caching, then the system uses minimal storage resources, but it cannot provide fast retrieval of previously processed data
Solution Approach 1:
The system performs preliminary geocoding operations and caches the results for future use. When location data is geocoded, the results are stored in a cache structure that enables rapid retrieval. This preliminary action of caching transforms the system from purely on-demand processing to one that anticipates and prepares for future requests, significantly reducing retrieval time for repeated queries.
3Loss of time
If all geocoding requests are processed in real-time, then the system provides immediate results, but it cannot leverage previously computed data to reduce processing time
Solution Approach 1:
The system implements a feedback mechanism where geocoding results are cached and fed back into the system for future use. When a geocoding request is received, the system first checks the cache for previously computed results before performing new geocoding operations. This feedback loop eliminates redundant processing, reducing time loss for repeated queries while maintaining high overall productivity by quickly serving cached results.
Data Source
AI summary
Some embodiments provide a non-transitory machine-readable medium that stores a program. The program receives, from a client device, a request to geo-enrich data that includes a set of data and a set of location data associated with the set of data. The program also selects a geocoder from a plurality of different geocoders based on the set of location data associated with the set of data. The program further geo-enriches the set of location data using the selected geocoder.