BriefGPT.xyz
Dec, 2016
共同批判: 好恶和特性的引出
Coactive Critiquing: Elicitation of Preferences and Features
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Stefano Teso, Paolo Dragone, Andrea Passerini
TL;DR
本文提出了一种偏好引导方法，扩展了合作式学习方法来收集用户的反馈信息，并且动态扩展特征空间以集成用户的批评，其中包括构造性学习任务，实证分析证明了本方法的优越性能及应用前景。
Abstract
When faced with complex choices, users refine their own preference criteria as they explore the catalogue of options. In this paper we propose an approach to
preference elicitation
suited for this scenario. We extend
co
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