Graphic Comparator With Property-Specific Weighting Coefficients
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Solution Overview
Problem
Existing comparison methods do not effectively weight individual user evaluations with property-specific coefficients, leading to incongruence in evaluating comparison targets based on user needs and desires.
Innovation Solution
A comparator system that calculates and applies property-specific weighting coefficients derived from reference user evaluations, allowing for more accurate alignment of user evaluations with the importance of properties, thereby enhancing the congruence percentage between user and reference user opinions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If property-specific weighting coefficients are applied to user evaluations, then the accuracy of representing user preferences is improved, but the complexity of the comparison system increases
Solution Approach 1:
The system pre-calculates property-specific weighting coefficients based on reference user evaluations before the actual comparison takes place. These coefficients are stored and ready to be applied when new user evaluations are received, eliminating the need for complex real-time calculations during the comparison process.
Solution Approach 2:
The weighting coefficients act as an intermediary element that bridges the reference user evaluations and the actual user evaluations. Instead of directly comparing raw evaluation values, the system uses these coefficients as a mediator to adjust and normalize the evaluations, simplifying the comparison process while improving accuracy.
2Reliability
If reference user evaluations are used to determine weighting coefficients, then the congruence between user and reference user opinions is improved, but the time required for evaluation and comparison increases
Solution Approach 1:
The system performs the time-consuming task of calculating weighting coefficients from reference user evaluations in advance, before the actual comparison needs to take place. This preliminary action separates the heavy computational work from the user interaction time, allowing rapid comparisons once the coefficients are ready.
Solution Approach 2:
The system uses the reference user evaluations themselves to generate the weighting coefficients, allowing the reference data to serve dual purposes: both as the basis for establishing importance weights and as part of the overall validation process. This self-service approach eliminates the need for separate calibration processes.
Data Source
AI summary
A method, a data network arrangement and a computer program product by which a comparator can be implemented in a data network. The user of the comparator stores his evaluation of the properties included in the targets to be evaluated in a database in the server in the data network using a graphic one- or two-dimensional evaluation frame. In the comparator the comparator user's evaluations are compared to property evaluations given by a reference user. When calculating the total accuracy percentage of the comparison the evaluations given by the comparator user are weighted with a weighting coefficient, which is obtained by normalizing first the importance evaluations of all the properties given by the reference user and by using the normalized importance evaluation of a certain property as the weighting coefficient for this property.