Radar-Chart Product Presentation for Multidimensional Preference Matching
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Solution Overview
Problem
Existing systems fail to accurately present information regarding products and beverages/foods that conform to a user's preferences, lacking detailed and personalized recommendations based on comprehensive sensory evaluation.
Innovation Solution
A device that includes a user preference evaluation value storage unit, item evaluation value storage unit, reception unit, determination unit, and product information presentation unit to match user preferences with item evaluations, using a radar chart to display coinciding products and beverages/foods, and optionally adjusting item evaluation values based on user attributes and history.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive sensory evaluation data is collected and stored for multiple users and items, then recommendation accuracy is improved, but device complexity and data storage requirements increase
Solution Approach 1:
The system segments preference evaluation into multiple independent sensory dimensions (taste, smell, texture, etc.), each with its own evaluation scale. This allows comprehensive evaluation without requiring a monolithic complex system, as each dimension can be processed and stored separately in the database.
Solution Approach 2:
The patent introduces a multi-dimensional evaluation space where preferences are represented across multiple sensory dimensions simultaneously. This dimensional approach allows accurate matching by comparing vectors in multidimensional space rather than using simple scalar comparisons, improving accuracy without proportionally increasing system complexity.
2Measurement precision
If detailed sensory evaluation topics are used for each item, then recommendation precision is improved, but information processing complexity increases
Solution Approach 1:
The system changes the parameter representation by using standardized numerical scales for each sensory dimension (e.g., sweetness from 1-10, acidity from 1-10). This parameter standardization allows detailed evaluation without proportionally increasing processing complexity, as numerical comparisons are computationally efficient compared to qualitative analysis.
Solution Approach 2:
Different items are evaluated with locally appropriate sensory dimensions and scales based on their characteristics. For example, beverages may emphasize taste and carbonation while foods emphasize texture and flavor profiles. This local customization allows precise evaluation without requiring all items to undergo identical complex evaluation processes.
3Adaptability or versatility
If user preference data and item evaluation data are stored and compared systematically, then personalized recommendation capability is improved, but data storage and processing requirements increase
Solution Approach 1:
The system extracts only the essential sensory evaluation parameters needed for matching rather than storing all possible item attributes. By focusing on the key sensory dimensions that users actually care about, the system achieves personalization capability with reduced data storage requirements compared to comprehensive item databases.
Solution Approach 2:
User preferences are pre-evaluated and stored as fixed numerical values across sensory dimensions before actual recommendation queries. This preliminary action allows the system to perform fast comparisons without re-evaluating preferences during each query, reducing real-time processing requirements and enabling efficient personalized recommendations.
Data Source
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AI summary
The present invention is capable of more accurately presenting a product, beverage or food which conforms to the preferences of a user in comparison to the prior art. In response to a presentation request, the present invention extracts a user preference evaluation value associated with the user from a user preference evaluation value storage unit, compares the extracted user preference evaluation value with a corresponding item evaluation value stored in an item evaluation value storage unit, and determines the degree of coincidence between the two values. The present invention presents information pertaining to a product which conforms to the preferences of a user according to the determination results.