POI Accuracy Workflow Using Ticket and Trip Log Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems that maintain catalogs of places of interest (POI) often face challenges in updating geographic coordinates when POIs close or move, leading to stale data due to slow or absent updates.
Innovation Solution
A networked system analyzes tickets and trip logs to determine a workflow for improving POI accuracy by extracting relevant data, identifying POI attributes, and triggering verification processes based on priority levels, which may involve human operators or user-generated content to verify addresses and coordinates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a catalog of POIs is maintained with geographic coordinates, then the system can provide location information for services, but the data becomes stale when POIs close or move because updates are slow or absent
Solution Approach 1:
The system performs preliminary actions by proactively detecting POI changes through multiple data sources (trip logs, tickets, user feedback) before the catalog becomes stale. Verification workflows are initiated in advance to confirm changes, ensuring the catalog is updated promptly rather than waiting for routine updates.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring trip logs, support tickets, and user reports for indicators of POI changes. When changes are detected, feedback loops trigger verification workflows that confirm the changes and update the catalog, creating a closed-loop system that maintains data accuracy through continuous validation.
2Measurement precision
If the system verifies POI accuracy through manual processes, then data accuracy improves, but the complexity of the system increases due to multiple verification steps and workflows
Solution Approach 1:
The verification system is segmented into distinct modular components: change detection modules that monitor different data sources (trip logs, tickets, user feedback), verification modules that validate specific types of changes, and update modules that apply confirmed changes. This segmentation allows each component to specialize in specific tasks, reducing overall system complexity while maintaining high accuracy.
Solution Approach 2:
The system introduces intermediary verification mechanisms between raw data and the final catalog update. Multiple layers of verification (automated checks, cross-referencing with external sources, user confirmation) act as intermediaries that filter and validate data before it enters the catalog, ensuring accuracy without requiring complete manual verification of every change.
3Measurement precision
If the system uses multiple data sources to detect POI changes, then the accuracy of detection improves, but the quantity of data to be processed increases
Solution Approach 1:
The system extracts only the relevant features and indicators from each data source that signal potential POI changes. Instead of processing entire trip logs or support tickets, the system extracts specific patterns (e.g., repeated visits to wrong locations, user complaints about closed businesses, geographic mismatches) and focuses verification efforts on these extracted signals, reducing data volume while maintaining detection accuracy.
Solution Approach 2:
The system applies different levels of processing intensity to different data sources based on their reliability and relevance. High-trust sources (e.g., multiple independent user reports of the same change) trigger immediate verification, while lower-trust sources require additional validation. This local quality approach optimizes processing resources by applying rigorous verification only where necessary.
Data Source
AI summary
Systems and methods for improving accuracy of geographic position data are provided. A networked system mines ticket data from content of the ticket. Based on the ticket data, a determination is made that the ticket indicates an issue with a trip involving a point of interest (POI). The networked system extracts trip data from a trip log corresponding to the trip involving the POI, and identifies, from a data storage, stored attributes of the POI. The networked system analyzes the ticket data, trip data, and attributes to determine a workflow to improve accuracy of the POI, whereby the analyzing comprises determining a priority level to verify accuracy of the POI. The workflow is triggered based on the priority level to verify accuracy of the POI.