{"title":"Popularity Preserving Fair Matching","authors":"Toru Nakamura, T. Isohara","doi":"10.1109/ESCI56872.2023.10099911","DOIUrl":null,"url":null,"abstract":"This paper discusses on the fairness on the context of two-sided matching. This paper proposes a new definition of individual fairness for two-sided matching, called Popularity Preserving Fairness (PPF). It is the first definition of individual fairness for two-sided matching that does not have to make the model more complex. The new definition of PPF means that the wish of a person with higher popularity takes priority over that of a lower person. This paper also proposes a relaxed version of PPF with thresholds $k, \\ell$ because a PPF matching does not always exist. The relaxed definition allows a person $B$ whose popular rank is below that of $A$ within $k$ to match a person whose rank in $B$'s preference order is lower than that of $A$ and lor regards the difference of ranks of matched people is within $\\ell$ as a not different case. Furthermore, this paper provides an efficient decision algorithm for PPF matching.","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ESCI56872.2023.10099911","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper discusses on the fairness on the context of two-sided matching. This paper proposes a new definition of individual fairness for two-sided matching, called Popularity Preserving Fairness (PPF). It is the first definition of individual fairness for two-sided matching that does not have to make the model more complex. The new definition of PPF means that the wish of a person with higher popularity takes priority over that of a lower person. This paper also proposes a relaxed version of PPF with thresholds $k, \ell$ because a PPF matching does not always exist. The relaxed definition allows a person $B$ whose popular rank is below that of $A$ within $k$ to match a person whose rank in $B$'s preference order is lower than that of $A$ and lor regards the difference of ranks of matched people is within $\ell$ as a not different case. Furthermore, this paper provides an efficient decision algorithm for PPF matching.
本文讨论了双边匹配背景下的公平性问题。本文提出了一种新的双边匹配下的个人公平的定义,称为人气保持公平(PPF)。这是第一个没有使模型变得更复杂的双边匹配的个人公平的定义。PPF的新定义意味着,受欢迎程度高的人的愿望优先于受欢迎程度低的人的愿望。本文还提出了一个放宽版本的PPF,其阈值为$k,因为PPF匹配并不总是存在。宽松定义允许在$k$范围内受欢迎排名低于$ a $的人$B$与在$B$偏好顺序中排名低于$ a $的人配对,并将配对者的排名差异在$\ well $范围内视为无差异情况。在此基础上,提出了一种高效的PPF匹配决策算法。