Adaptive Tire Recommendation System Using User Comprehension Assessment
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Solution Overview
Problem
Existing techniques for recommending automotive tire products to customers lack accuracy and effectiveness in tailoring recommendations to individual customer needs and vehicle use.
Innovation Solution
A method and system that dynamically assess a user's comprehension level regarding tire products by iteratively presenting questions and adjusting subsequent queries based on responses, allowing for personalized estimation of vehicle use and customer value to specify appropriate tire product recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional tire recommendation techniques are used, then the recommendation process is simple, but the accuracy of recommendations fails to meet individual customer needs
Solution Approach 1:
The system dynamically adjusts the questioning process based on user comprehension level. Questions are adaptively selected and modified in real-time according to how well the user understands tire product concepts, transforming a static recommendation system into a dynamic one that responds to user feedback
Solution Approach 2:
The system implements feedback loops where user responses to questions are continuously analyzed to determine comprehension level. This feedback is then used to adjust subsequent questions and refine the recommendation, creating a closed-loop system that improves accuracy through iterative learning
2Measurement precision
If multiple questions are asked to assess comprehension level, then recommendation accuracy improves, but the time required for the process increases
Solution Approach 1:
The system asks only the necessary number of questions to achieve sufficient comprehension assessment. Rather than asking all possible questions, it selectively asks partial sets based on what is needed to determine the user's level, avoiding excessive questioning while maintaining assessment accuracy
Solution Approach 2:
The system performs preliminary assessment with a small initial set of questions to quickly determine the user's comprehension level. This preliminary action allows the system to then tailor the remaining questioning process, avoiding the need to ask all questions regardless of user level
Data Source
AI summary
A method executed by a computer, including: executing multiple times a first process of outputting question information to a user and acquiring response information from the user; executing a second process at least once while executing the first process multiple times; executing a third process of estimating a vehicle use and customer value for the user and specifying one or more tire products to recommend to the user based on two or more pieces of the response information acquired; and outputting information indicating the vehicle use and the customer value estimated and information regarding the one or more tire products specified. The second process includes determining a comprehension level of the user regarding a tire product, based on one or more pieces of the response information acquired, and determining question information to be output next time and thereafter, according to the comprehension level determined.