Dynamic User Experience Design Selection via Inference Manager
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Solution Overview
Problem
Current user experience design selection methods face challenges in making informed decisions in time-critical environments with limited information, often resulting in generic designs that fail to satisfy diverse client types, leading to poor user experiences and reduced appeal of products or services.
Innovation Solution
Implementing an inference manager that initiates multiple inference processes to classify clients based on varying amounts and sources of information, selecting a user experience design based on the most accurate results within a predefined time, allowing for tailored and dynamic user experiences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple inference processes are initiated to classify clients accurately, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system dynamically adjusts the number and complexity of inference processes based on available time resources. The inference manager can initiate one or multiple inference processes depending on the time remaining before a design selection is needed, allowing the system to adapt its classification accuracy efforts to the temporal constraints of each situation.
Solution Approach 2:
The system performs partial classification actions by initiating only the necessary number of inference processes to achieve sufficient accuracy within the available time. Rather than always running all possible inference processes, the system selects an appropriate subset based on time constraints, achieving adequate classification without unnecessary time expenditure.
2Device complexity
If generic user experience designs are used, then device complexity is reduced, but adaptability worsens
Solution Approach 1:
The system segments the user experience design space into multiple distinct designs (e.g., performance-oriented, cost-oriented, balanced designs) that can be selectively applied based on client classification. This segmentation allows the system to maintain simplicity by using discrete, pre-defined design options while achieving adaptability through intelligent selection among these segments based on inferred client characteristics.
3Adaptability or versatility
If tailored user experience designs are provided, then adaptability is improved, but device complexity increases
Solution Approach 1:
The inference manager acts as an intermediary that simplifies the complexity of selecting tailored user experience designs. Rather than requiring the entire system to handle complex customization logic, the inference manager receives client information, runs appropriate inference processes, and outputs a classification that directly maps to specific design selections, thereby managing complexity centrally while enabling adaptability throughout the system.
Data Source
AI summary
Various embodiments are generally directed to techniques for selecting a user experience design in a time-critical environment, such as based on the results of multiple classification processes while maintaining appropriate responsiveness, for instance. Some embodiments are particularly directed to selecting a website design experience based on results, or lack thereof, provided by a plurality of inference processes of varying accuracy within a predefined amount of time. For example, a page request, or indication thereof, may be received by an inference manager from a client device. In response to the page request, the inference manager may initiate one or more inference processes, and based on the response, or lack thereof, from each of the one or more inference process within a predetermine amount of time, the inference manager may provide an indication to an experience design selector. The experience design selector may then select, based on the indication, from a plurality user experience designs to provide to the client device in a page response.