Product Selection System Using User-Specific Value Normalization
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Solution Overview
Problem
Shoppers face difficulty in selecting products due to the complexity of evaluating numerous attributes across various products, with scattered information making it time-consuming to determine which attributes align with their objectives.
Innovation Solution
A system and process for recommending products by determining user-specific product values based on user-defined attribute preferences, normalizing these values against baseline values, and calculating product scores to facilitate efficient selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the number of products and product attributes to evaluate is increased, then the comprehensiveness of product selection improves, but the time and complexity of the selection process increases
Solution Approach 1:
The patent segments the complex product selection process into distinct components: (1) identifying user objectives, (2) translating objectives into product attributes, (3) normalizing attribute values, and (4) ranking products. This segmentation allows the system to handle multiple attributes systematically without overwhelming the user, reducing selection time while maintaining comprehensive evaluation.
Solution Approach 2:
The patent introduces an intermediary computational system that acts as a mediator between user objectives and product selection. This system automatically translates objectives into attributes, normalizes values across different products, and generates rankings, eliminating the need for users to manually evaluate each attribute and significantly reducing selection time.
2Adaptability or versatility
If product information is scattered across different sources, then the variety of available products increases, but the difficulty of gathering and evaluating information increases
Solution Approach 1:
The patent merges scattered product information from multiple sources into a unified evaluation framework. By consolidating attributes from different products into a common structure with standardized normalization, the system enables comprehensive comparison across diverse product types without requiring users to manually gather and organize information from scattered sources.
Solution Approach 2:
The patent creates a universal evaluation system that can handle multiple product types and attributes through a single framework. The objective-to-attribute translation mechanism and normalization process work universally across different product categories, allowing the system to adapt to various product varieties while maintaining consistent evaluation procedures.
3Measurement precision
If the number of product attributes to evaluate is increased, then the alignment with user objectives improves, but the difficulty of understanding which attributes matter increases
Solution Approach 1:
The patent performs preliminary action by pre-translating user objectives into specific product attributes before the actual product evaluation. This upfront translation step identifies which attributes are relevant to each user's objectives, eliminating the need for users to understand or evaluate irrelevant attributes and reducing the perceived complexity of the selection process.
Solution Approach 2:
The patent replaces the mechanical cognitive process of manually evaluating attribute importance with an automated computational system. The system automatically translates objectives into attributes, determines which attributes matter for each user, and performs normalization and ranking, substituting human cognitive effort with algorithmic processing that handles attribute importance identification seamlessly.
Data Source
AI summary
Techniques for selecting a product are disclosed. A user-specific product value specific to a user is determined for each of at least a subset of a set of a plurality of products. The user-specific product value is based at least in part on a user-specific product attribute value associated with a product attribute specific to the user. A product is selected from the set of a plurality of products, the selection is based at least in part on the determined user-specific product values.