Geocoding System Token Parsing Multi-Source Candidate Comparison
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional geocoders are limited to a single data set and format, lacking flexibility and requiring significant efforts to change data sets, which restricts their ability to compare information from different data sets for optimal output.
Innovation Solution
A computer-implemented method and system that processes geographic data by parsing queries into tokens, sending them to multiple harvesters, comparing candidates from different data sources, and returning accurate geographic locations through scoring and multiple rounds of candidate gathering, including exact, interpolated, non-exact, and partial matches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional geocoders are designed to work with a single data set and format, then they can maintain simple structure and operation, but they lack flexibility and cannot compare information from different data sets
Solution Approach 1:
The system segments the geocoding process into distinct functional modules: a parser that tokenizes input addresses, multiple independent harvesters that query different data sets, and a scorer that evaluates candidates. This segmentation allows each component to remain simple while the integrated system achieves high adaptability across multiple data sets.
Solution Approach 2:
The geocoder is designed as a universal system that can process queries across multiple different data sets and formats simultaneously. The parser uses format-agnostic tokenization, and harvesters are configured to query different data sources using standardized interfaces, enabling the system to adapt to various data formats without requiring format-specific processing logic.
2Adaptability or versatility
If conventional geocoders are limited to a single data set, then they require minimal configuration efforts, but they require significant efforts to change data sets when needs change
Solution Approach 1:
The system employs dynamic configuration where harvesters can be enabled or disabled based on the query type and available data sets. The parser dynamically adjusts tokenization based on input format, and the scorer dynamically weights candidates from different harvesters. This dynamic behavior allows rapid adaptation to different data sets without reconfiguring the entire system architecture.
Solution Approach 2:
The system changes operational parameters rather than structural components when adapting to different data sets. Configuration parameters such as harvester weights, query thresholds, and data set priorities can be adjusted to optimize performance for different data sources without modifying the underlying code or system structure.
3Measurement precision
If conventional geocoders use a single data set, then they can provide quick results, but they lack the ability to compare information to provide the best output
Solution Approach 1:
The system performs partial comparisons by evaluating candidates from multiple harvesters and selecting the best match without requiring exhaustive analysis of all possible data sources. The scorer ranks candidates and returns results after evaluating sufficient alternatives, providing high accuracy without the computational overhead of complete enumeration.
Solution Approach 2:
The scorer provides feedback by evaluating and ranking candidates from different harvesters, using scoring mechanisms to determine the quality and relevance of each match. This feedback loop allows the system to efficiently identify the best geographic location by comparing candidates and selecting those with highest scores, balancing accuracy and processing speed.
Data Source
AI summary
Systems, methods, and computer-readable media are provided for processing geographic data and identifying geographic locations. In one implementation, a computer-implemented method is provided that is performed by one or more processors, the method comprising operations including receiving a query including an address, parsing the address into tokens, and sending the tokens to one or more harvesters. The method also includes receiving one or more geographic location candidates from the one or more harvesters in response to the tokens, comparing the one or more candidates, and returning one or more geographic locations based on the comparison.