Similarity Calculation Using User Preference Weighting
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Solution Overview
Problem
Existing systems for calculating the degree of similarity between evaluation targets fail to adequately reflect the subjectivity of the user in the evaluation process.
Innovation Solution
A degree-of-similarity calculation system that sets multiple evaluation items with attribute values for each target, incorporates an evaluation information acquisition unit, a degree-of-similarity calculation unit, and a preference information acquisition unit to calculate similarity based on user preferences and selected evaluation items.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a system calculates the degree of similarity between evaluation targets using conventional methods, then the calculation can be performed objectively based on data, but the result does not sufficiently reflect the subjectivity of the user
Solution Approach 1:
The system performs preliminary actions by acquiring user preference information before calculating similarity. The preference information acquisition unit collects data about user preferences in advance, which is then used to weight evaluation items during the similarity calculation process, ensuring user subjectivity is reflected from the outset
Solution Approach 2:
The system changes parameters by introducing weights to evaluation items based on user preferences. The degree-of-similarity calculation unit modifies the calculation parameters by applying different weights to different evaluation items, transforming the calculation from a uniform objective measure to a customized measure that reflects individual user subjectivity
2Measurement precision
If multiple evaluation items are used to calculate similarity, then the assessment becomes more comprehensive, but the complexity of the calculation system increases
Solution Approach 1:
The system segments the similarity calculation process into distinct functional units: an evaluation information acquisition unit that collects data on multiple evaluation items, a preference information acquisition unit that gathers user preferences, and a degree-of-similarity calculation unit that processes the information. This segmentation manages complexity by organizing the comprehensive assessment into modular, manageable components
Solution Approach 2:
The system introduces preference information as an intermediary element that mediates between the multiple evaluation items and the final similarity calculation. This intermediary (preference information) helps manage the complexity by providing a structured way to incorporate user subjectivity without requiring direct complex interactions between all evaluation items
Data Source
AI summary
A plurality of evaluation items for evaluating similarity between a plurality of evaluation targets is set for each of the evaluation targets, and an attribute value is set for each of the evaluation items of each of the evaluation targets. The attribute value indicates a degree of an attribute of each of the evaluation targets for each of the evaluation items. A degree-of-similarity calculation system includes: an evaluation information acquisition unit configured to acquire information on attribute values of each evaluation item of each evaluation target; and a degree-of-similarity calculation unit configured to calculate a degree of similarity between evaluation targets based on attribute values of the evaluation items selected by the user or corresponding to the preference of the user.