Latent ranking analysis using pairwise comparisons in crowdsourcing platforms

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• 作者：Younghoon Kim^a ; Wooyeol Kim^b ; Kyuseok Shim^b ; ^{shim@kdd.snu.ac.kr}
• 关键词：Learning to rank ; Pairwise comparison ; Active learning ; Crowdsourcing
• 刊名：Information Systems
• 出版年：2017
• 出版时间：April 2017
• 年：2017
• 卷：65
• 期：Complete
• 页码：7-21
• 全文大小：2512 K
• 卷排序：65

文摘

We study how to learn multiple latent rankings from pairwise comparisons. We propose a novel probabilistic model to capture the process of pairwise comparison. We develop an efficient inference algorithm to learn multiple latent rankings. We also investigate active learning problem considering crowdsourcing platforms. Experiments with synthetic and real life data show the effectiveness of our algorithms.