Visit Assignment for Partially Observable Location Data Streams
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Solution Overview
Problem
Existing systems face challenges in accurately assigning visits to location data streams due to noise and errors in location data, varying data representations, and the need for scalable solutions to handle large volumes of contextually relevant data in real-time, especially for offline user journeys.
Innovation Solution
A method and system for automatically assigning visits to partially observable location data streams by identifying power-law characteristics, determining a region of uncertainty, filtering data, clustering dimensions, generating confidence scores, and assigning visits to points of interest using a linear scoring model, while ensuring data validity and privacy compliance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If location data streams are processed from multiple sources to improve coverage and understanding of user behavior, then the quantity and diversity of data increase, but the noise and errors in the data also increase
Solution Approach 1:
The patent combines multiple location data streams from different sources (GPS, Wi-Fi, Bluetooth, mobile network) into a unified data model. By merging these diverse data sources and applying consistent processing rules, the system achieves comprehensive coverage while maintaining data quality through the integration of complementary information from each source.
Solution Approach 2:
The patent introduces an intermediary processing layer that acts as a mediator between raw location data streams and the final geo-spatial model. This intermediary layer includes modules for data validation, noise filtering, and quality assessment that reconcile the conflicting needs of data quantity and reliability by selectively processing and weighting data from different sources.
2Loss of time
If real-time processing is implemented to maintain context relevance of location data, then the timeliness of data utilization improves, but the computational complexity and resource requirements increase
Solution Approach 1:
The patent segments the real-time processing system into distinct modular components: data ingestion modules, validation modules, filtering modules, and model updating modules. Each segment handles specific tasks independently, allowing the system to process location data in real-time while maintaining manageable complexity through clear separation of concerns and specialized processing pipelines.
Solution Approach 2:
The patent implements preliminary filtering and validation actions on location data streams before they are fully processed and integrated into the geo-spatial model. By pre-processing data to remove obvious noise and validate format compliance early in the pipeline, the system reduces the computational burden on subsequent real-time processing stages while maintaining data quality and context relevance.
3Measurement precision
If comprehensive filtering and validation are applied to ensure data quality, then the accuracy of visit assignment improves, but the processing time and computational resources increase
Solution Approach 1:
The patent applies local quality principles by implementing different filtering and validation strategies for different data sources and different types of location events. Instead of applying uniform comprehensive validation to all data, the system tailors the strictness and type of validation to the specific characteristics of each data source and the importance of the particular location event, thereby maintaining high accuracy while avoiding unnecessary processing overhead.
Solution Approach 2:
The patent dynamically adjusts processing parameters such as filtering thresholds, validation strictness, and clustering sensitivity based on the characteristics of the incoming data and the current state of the geo-spatial model. By changing parameters adaptively rather than using fixed comprehensive validation rules, the system maintains high visit assignment accuracy while optimizing processing speed for different operating conditions.
Data Source
AI summary
A system and method for automatically assigning visits to partially observable location data streams to maintain a geo-spatial model of a real world are provided. The method includes identifying a subset of a plurality of data streams that have a power-law characteristic in a time dimension or spatial dimension associated with the activity of the plurality of entities, modelling an activity of the plurality of entities to determine a region of uncertainty, obtaining a filtered activity of the entities, clustering the time dimension and the spatial dimension of the filtered activity using a stay points clustering method to generate at least one valid data stream, generating a confidence score for the at least one valid data stream, and assigning a visit of the plurality of entities to a point of interest (POI) based on the confidence score of the at least one valid data stream.