Location Model Generation for Frequent Destination Identification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current techniques face challenges in accurately determining locations of interest and identifying user visits, as existing location databases often lack sufficient information for various points of interest, making it difficult to provide accurate location-based services.
Innovation Solution
The system analyzes user location data from GPS-enabled devices and other sources to determine frequent destinations, generates location models, and identifies points of interest, enabling the identification of user visits and categorization of visit types based on duration and purpose.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing location databases are used, then location information can be provided to users, but the accuracy and completeness of location information for points of interest is insufficient
Solution Approach 1:
The system enables points of interest to self-report their locations and operational statuses directly to the information provision system. This self-service mechanism allows POIs to update their own information, ensuring both accuracy (through direct reporting) and completeness (through continuous updates), thereby resolving the contradiction between information accuracy and completeness
Solution Approach 2:
The system implements feedback mechanisms where user visits and interactions with points of interest are tracked and used to refine location information. This feedback loop continuously improves the accuracy and completeness of location data by incorporating real-world usage patterns and verification from actual user behavior
2Measurement precision
If user location data is collected and analyzed, then locations of interest and user visits can be accurately determined, but the complexity of the system increases
Solution Approach 1:
The system segments the complex task of location analysis into distinct functional modules: location data collection, trajectory generation, point of interest identification, and visit detection. Each module handles a specific aspect of the analysis, reducing overall system complexity while maintaining high accuracy in identifying user visits and locations of interest
Data Source
AI summary
Techniques are described for determining locations of interest based on user visits. In some situations, the techniques include obtaining information about actual locations of users at various times, and automatically analyzing the information to determine particular locations in a geographic area that are of interest, such as for frequent destinations visited by users. After determining a particular location of interest, it may be represented by generating a corresponding location model to describe the geographic subarea or other location point(s) covered by the determined location of interest, and one or more points of interest (e.g., businesses, parks, schools, landmarks, etc.) may be identified that are located at or otherwise correspond to the determined location of interest. In addition, a determined location of interest may be further used in various ways, including to identify later user visits to that location (e.g., to a point of interest identified for the location).