RozaAbolghasemi/GRS_crGAN
Adversarial Preference Learning with Pairwise Comparisons for Group recommendation System
This tool helps facilitate group decision-making by predicting food preferences for a group based on individual pairwise comparisons. You input data from an online experiment where experts provide scores for different food pairs, and it outputs recommendations for food choices that align with the group's collective taste. This is ideal for researchers studying consensus-building and group dynamics in preference elicitation.
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Use this if you are a researcher analyzing group preferences for items like food and need to predict missing preferences from pairwise comparison data.
Not ideal if you need a real-time, production-ready recommendation system for a large user base or a system that doesn't rely on pairwise comparison data.
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MIT
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Last pushed
Feb 29, 2024
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