Location-Based Activity Data Extraction for User Service Expectation Analysis
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Solution Overview
Problem
Conventional information providing devices struggle to grasp the services expected by users who have visited specific facilities or regions, as they primarily focus on similarities between user activities without considering location-based data effectively.
Innovation Solution
An apparatus and method that acquire location information of multiple users, extract users who have visited specific spots during predetermined periods, and generate activity data on the users' movements before and after visiting those spots, using this information to analyze user preferences and expected services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional information providing devices determine similarities between users of activities recorded by users independently, then user activity similarity can be analyzed, but the service expected by users who have visited a particular facility or region cannot be grasped
Solution Approach 1:
The patent segments user activity data into two distinct types: general activity data (independent user activities) and location-based activity data (activities at specific facilities or regions). This segmentation allows the system to process and analyze different aspects of user behavior separately, thereby capturing location-specific service expectations without overwhelming complexity in the data processing system.
Solution Approach 2:
The patent introduces location information as an intermediary element that connects user activities to specific facilities or regions. By using location data as a mediator, the system can infer service expectations based on where users have been, rather than relying solely on independent activity records, thus reducing information loss while maintaining manageable system complexity.
2Loss of information
If location information of multiple users is acquired and analyzed to grasp service expectations, then understanding of user preferences improves, but data acquisition and processing requirements increase
Solution Approach 1:
The patent extracts and focuses on location-based activity data specifically associated with facilities or regions where users have been. By selectively extracting only the relevant location information rather than processing all user data, the system can grasp service expectations effectively while managing the quantity of data that needs to be processed.
Solution Approach 2:
The patent applies local quality analysis by examining user activities at specific locations (facilities or regions) rather than treating all user data uniformly. This approach allows the system to focus computational resources on analyzing location-specific patterns, thereby reducing the overall data processing burden while capturing meaningful user preference information.
Data Source
AI summary
An apparatus includes processing circuitry configured to: acquire location information of a plurality of users; extract, from the location information of the plurality of users, a user who has visited a predetermined spot during a predetermined period; and generate, as activities-on-that-day data, data on where the user has been during preceding and subsequent periods per a predetermined unit time relative to a timing when the spot has been visited by the user who has visited the predetermined spot based on the location information of the extracted user.