Detecting POI Closure via Trip Data Time Buckets
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Solution Overview
Problem
Existing systems face challenges in accurately updating point of interest (POI) data due to slow or incomplete updates when POIs close or move, leading to outdated information in catalogs.
Innovation Solution
A networked system processes trip data to detect and verify changes in POI attributes by generating time buckets, calculating trip counts, and using machine learning algorithms like the Markov chain algorithm to determine declines in activity, triggering verification processes through user interfaces for confirmation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If manual updating methods are used for POI catalogs, then implementation simplicity is maintained, but update speed and accuracy deteriorate
Solution Approach 1:
The patent replaces manual mechanical updating processes with automated electronic data processing. The system automatically collects trip data, processes it through algorithms to detect POI changes, and updates catalogs without human intervention, thereby increasing update speed while accepting the introduction of computational systems.
Solution Approach 2:
The system enables self-service by automatically detecting POI closures and moves through analysis of trip data patterns. The automated detection mechanism monitors trip counts over time periods, identifies anomalies indicating POI status changes, and triggers updates autonomously, eliminating the need for manual catalog maintenance.
2Measurement precision
If automated detection systems are implemented, then update accuracy improves, but system complexity increases
Solution Approach 1:
The detection system is segmented into distinct functional modules: trip data collection, time bucket generation, trip count calculation, change detection algorithms, and catalog update mechanisms. This modular architecture improves detection accuracy while managing complexity through organized, independent components that can be developed and maintained separately.
Solution Approach 2:
The patent introduces intermediate data structures and processing layers between raw trip data and final catalog updates. Time buckets serve as intermediaries to aggregate trip data over periods, and detected changes act as intermediaries between monitoring and updating systems, thereby improving detection accuracy while isolating complexity into manageable intermediate layers.
3Loss of time
If frequent monitoring is performed, then data freshness improves, but computational resource consumption increases
Solution Approach 1:
The system implements periodic monitoring by dividing time into discrete buckets and analyzing trip data at regular intervals rather than continuously. This periodic approach ensures data freshness by systematically updating catalogs at defined periods while conserving computational resources by avoiding constant monitoring and processing.
Solution Approach 2:
The system performs partial monitoring by focusing computational resources on detecting specific changes (closures and moves) rather than analyzing all possible POI attribute modifications. This selective approach maintains data freshness for critical changes while reducing overall computational resource consumption by not exhaustively processing every potential data variation.
Data Source
AI summary
Systems and methods for detecting and verifying closed places (e.g., claims no longer in business) from trip data are provided. A networked system accesses trip data associated with the POI. The networked system processes the trip data to generate at least two time buckets based on timestamps from the trip data associated with the POI, and calculates trip counts associated with the POI for each of the time buckets. Using a machine learning algorithm and based on the at least two time buckets, the networked system determines that the trip counts show a decline over time that indicates that the POI is likely closed. In response to the determining, the networked system updates a database to indicate the POI is closed.