User Profile Generation via Continuous Sentiment Parameter Adjustment
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Solution Overview
Problem
Conventional user profiling methods, such as standardized questionnaires, lack flexibility and accuracy due to standardized questions with limited discrete options, leading to potential muscle memory responses and reduced user engagement, resulting in incomplete or inaccurate profiles.
Innovation Solution
A system that generates user profiles based on user sentiment metrics by adjusting visual and audible representations of these metrics, allowing users to input feelings intuitively through proportional, brightness, hue, saturation, volume, and tone adjustments, with dynamic and variable sentiment analysis, and incorporating sensor and environmental data for a more comprehensive profile.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If standardized questionnaires are used to generate user profiles, then the method is simple and easy to implement, but the accuracy and flexibility of the profile is reduced due to limited discrete options
Solution Approach 1:
The patent transforms the questionnaire from a discrete option format to a continuous parameter adjustment format. Users can dynamically adjust visual parameters (size, brightness, color intensity) and audible parameters (volume, tone) to represent their sentiment magnitude, enabling continuous rather than discrete measurement of user sentiments.
Solution Approach 2:
The patent adds visual and audible dimensions to the traditional text-based questionnaire. By representing sentiment metrics through visual characteristics (size, brightness, hue, saturation) and audible characteristics (volume, tone), the system creates multiple dimensions for users to express their feelings, thereby improving measurement precision.
2Stability of the object's composition
If the same questionnaire is repeated to obtain updated user profiles, then the process is consistent and systematic, but user engagement decreases leading to muscle memory responses and reduced accuracy
Solution Approach 1:
The patent introduces dynamic and interactive elements to the profile update process. Instead of static questionnaire items, users dynamically adjust visual and audible representations of their sentiments. The system can also dynamically change the presentation of metrics between updates, maintaining process consistency while preventing muscle memory effects.
Solution Approach 2:
The patent replaces the mechanical act of reading and selecting from text options with more engaging sensory interactions. Users manipulate visual elements (resizing, brightness adjustment, color selection) and audible elements (volume, tone), creating a more engaging experience that reduces automatic responding.
3Device complexity
If discrete options are provided in questionnaires, then the questionnaire structure is simple and standardized, but the user's actual sentiments may not be accurately captured
Solution Approach 1:
The patent changes the measurement parameter from discrete categorical options to continuous adjustable parameters. Users can fine-tune the magnitude of their sentiments by adjusting visual and audible characteristics, allowing for precise expression of their actual feelings rather than being constrained to predefined discrete levels.
Data Source
AI summary
The invention provides a system for obtaining a user profile comprising one or more user sentiment metrics. The system includes a display unit adapted to display a representation of each of the one or more user sentiment metrics, each representation occupying a proportion of a display area of the display unit, and a user interface in communication with the display unit adapted to receive a user input. The system further comprises a processing unit, in communication with the display unit and the user interface, adapted to control the display unit to adjust a characteristic of the representation of a user sentiment metric based on the user input, the characteristic of the representation of a user sentiment metric representing the magnitude of the user sentiment metric and generate a user profile based on the adjusted characteristic of each representation of the one or more user sentiment metrics.