Dynamic Value Ranking for Personalized Decision Support
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Solution Overview
Problem
Current systems for making decisions and purchases rely on fixed personal values that do not account for changes over time, leading to predictions that may not align with a user's current perspectives, as they fail to consider dynamic and evolving values such as social circles, socioeconomic background, race, and gender.
Innovation Solution
A method that uses a device to receive registration information including demographic perspectives, searching for options based on fixed, changing, and hybrid values, comparing and ranking them to determine an optimal fit that aligns with the user's current values, incorporating cultural and social values that may evolve over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed set of personal values is used to make predictions on user decisions and purchases, then the system maintains simplicity and consistency, but the predictions fail to account for changes in user values over time, reducing accuracy and relevance
Solution Approach 1:
The patent implements a dynamic value system where personal values are no longer fixed but evolve over time through multiple updating mechanisms. The system transitions from static value sets to dynamic value sets that automatically update based on user interactions, demographic data changes, and behavioral patterns, allowing predictions to remain accurate without requiring complete system redesign
Solution Approach 2:
The patent segments personal values into multiple independent dimensions including demographic values, social circle values, cultural values, and individual preference values. Each dimension can be updated and weighted independently, allowing the system to manage complexity through modular organization while improving prediction accuracy by considering multiple value aspects simultaneously
2Adaptability or versatility
If the system incorporates multiple evolving value sets including demographic perspectives, social circles, and cultural values, then it can account for user changes over time, but the system complexity increases significantly
Solution Approach 1:
The patent creates a universal value management system that handles multiple types of values (demographic, social, cultural, personal) through a single integrated framework. The same computational infrastructure processes all value types, and the system performs multiple functions including value storage, updating, weighting, and aggregation within one unified structure, reducing overall complexity despite the diversity of value sources
Solution Approach 2:
The patent introduces intermediary components including value weights, aggregation algorithms, and normalization layers that mediate between multiple complex value sources and the final prediction output. These intermediaries simplify the integration process by standardizing how different value sets are combined, making the system more manageable despite incorporating numerous evolving value dimensions
3Productivity
If predictions are made based on static personal values from a fixed time, then the system operates efficiently with simple computations, but the endpoint decisions may not align with the user's current evolving personal perspective values
Solution Approach 1:
The patent implements preliminary updating of value sets at scheduled intervals and upon triggering events, so that when predictions are made, the system already has current value information ready. This preliminary action ensures value alignment accuracy without requiring complex real-time computations during the actual decision-making process, maintaining efficiency while improving precision
Data Source
AI summary
A method includes a device receiving registration information indicating a demographic perspective that includes cultural and social values. A processor within the device searches for a series of potential options based on the registration information. The processor also searches for the potential options based on an initial set of fixed values, a changing set of values, and a hybrid set of values. The device compares the series of potential options based on the initial set of values, changing set of values, hybrid set of values, and demographic perspective. The device also appraises the series of options, wherein the device performs an ordering and/or ranking of the potential options. The device also identifies an optimal fit based on the ordering and/or ranking of the potential options.