POI Recommendation Boundary Expansion for GPS Drift Handling
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Solution Overview
Problem
Existing POI-based information recommendation systems lack accuracy due to GPS positioning errors, leading to misjudged encircling region states and wasteful consumption of computing resources.
Innovation Solution
Determine an encircling region with an expanded outer boundary based on the original boundary and positioning drift, using historical and real-time data to accurately represent the location relationship between a terminal device and the region, controlling information output through a location service accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If information recommendation is performed based on positioning signals alone, then the system is simple to implement, but the accuracy of information recommendation is low
Solution Approach 1:
The encircling region is divided into two boundaries: an inner boundary (original boundary) and an outer boundary (expanded boundary). This segmentation allows the system to distinguish between different location states (inside inner boundary, between boundaries, outside outer boundary) and make more accurate recommendations based on the terminal's specific position relative to these segmented regions.
Solution Approach 2:
The system performs preliminary expansion processing on the original boundary to create the outer boundary before determining location relationships. This preliminary action establishes a buffer zone that accounts for positioning drift in advance, enabling more accurate state determination without requiring complex real-time adjustments during operation.
2Reliability
If the encircling region boundary is expanded to account for positioning drift, then the accuracy of location state determination is improved, but the computing resources consumed increase
Solution Approach 1:
The boundary expansion is performed as a preliminary action during system setup or when POI information is retrieved, rather than performing complex expansion calculations in real-time during location state determination. This pre-computation approach reduces the computing burden during actual operation while still achieving accurate location state determination.
Solution Approach 2:
The system dynamically adjusts the boundary expansion based on the specific requirements of different POIs and location scenarios. The expansion is not applied uniformly to all regions but is selectively applied where needed, optimizing the balance between accuracy and computing resource consumption.
3Measurement precision
If real-time state determination is performed based on historical state and candidate location relationships, then the accuracy of information recommendation is improved, but the processing time increases
Solution Approach 1:
Candidate location relationships between the terminal and the boundaries are determined as a preliminary step before final state determination. This pre-computation of potential relationships allows the system to quickly arrive at the correct real-time state without performing exhaustive calculations during the actual state determination process.
Solution Approach 2:
The system uses historical state information as feedback to guide the current state determination process. By incorporating historical context, the system can make more informed decisions about the current location state, reducing the need for time-consuming recalculations from scratch.
Data Source
AI summary
A point of interest (POI)-based information recommendation method and apparatus, an electronic device, and a computer-readable storage medium are provided. The method includes: determining an encircling region encircling a POI in an electronic map; using an original boundary of the encircling region as an inner boundary and performing expansion processing on the inner boundary, to obtain an outer boundary of the encircling region; determining candidate location relationships between a terminal device and the inner boundary and the outer boundary according to positioning data of the terminal device; determining a real-time state according to a historical state of the terminal device and the candidate location relationships, the real-time state being used for representing a location relationship between the terminal device and the inner boundary; and controlling, according to the real-time state, information about the POI outputted through a location service.