Dynamic Location Attribute Estimation From User Visitation Patterns
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Solution Overview
Problem
Existing systems fail to accurately estimate the dynamic attributes of locations based on actual usage patterns, relying on static and administrator-determined genre information.
Innovation Solution
An estimation system that utilizes a learning model to analyze the positional relationships between locations visited by users, incorporating factors like usage count, age, and residence to predict future visitation patterns, especially for novice users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If static shop genre information specified in advance is used, then the system is simple to operate, but the estimation accuracy of location attributes deteriorates
Solution Approach 1:
The patent transforms the static shop genre information into dynamic location attributes by continuously updating them based on actual user visitation patterns. The system calculates visitation frequencies and updates attributes in real-time, making the information adaptive rather than fixed. This resolves the contradiction by maintaining operational simplicity while achieving high estimation accuracy through dynamic data refreshment.
Solution Approach 2:
The system implements feedback loops where user visitation data is continuously collected, processed, and used to refine location attributes. The calculated visitation frequencies feed back into the attribute estimation system, improving accuracy over time. This feedback mechanism allows the system to maintain simplicity while progressively enhancing estimation precision through learned patterns.
2Device complexity
If administrator-determined genre information is used, then the device complexity is low, but the reliability of location attributes deteriorates
Solution Approach 1:
The system enables location attributes to self-update based on actual user behavior data without requiring continuous administrator intervention. The automatic calculation of visitation frequencies and dynamic attribute updates allow the system to maintain low complexity while achieving high reliability through data-driven self-correction and adaptation.
3Loss of information
If static genre information is used, then the loss of information is minimal, but the adaptability to individual user behaviors deteriorates
Solution Approach 1:
The patent applies local quality by customizing location attributes for individual users based on their specific visitation patterns. Instead of using uniform static genres for all users, the system calculates and applies personalized attributes that reflect each user's unique behavior. This maintains information efficiency while achieving high adaptability to individual preferences and habits.
Data Source
AI summary
Provided is an estimation system including at least one processor configured to: acquire position information on a position of another location visited by a user who has visited an estimation target location which is a location for which an attribute is to be estimated; acquire a positional relationship between a position of the estimation target location and the position indicated by the position information; and estimate the attribute of the estimation target location based on the positional relationship.