A supervised learning approach to rankability

IF 4.1 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Nathan McJames , David Malone , Oliver Mason
{"title":"A supervised learning approach to rankability","authors":"Nathan McJames ,&nbsp;David Malone ,&nbsp;Oliver Mason","doi":"10.1016/j.cor.2025.107049","DOIUrl":null,"url":null,"abstract":"<div><div>The rankability of data is a novel problem that considers the ability of a dataset, represented as a graph, to produce a <em>meaningful</em> ranking of the items it contains. To study this concept, a number of rankability measures have been proposed, based on comparisons to a complete dominance graph via combinatorial and linear algebraic methods. Interest in this field has been steadily expanding, with a growing appreciation for the significance of evaluating rankability across diverse applications. Consequently, the validation of these rankability methodologies in different scenarios holds paramount importance. In this paper, we review existing measures of rankability and highlight some questions to which they give rise. We go on to introduce a new framework designed to evaluate rankability with a tailored approach, one that allows for efficient estimation in specific problem domains. Finally, we present a comparative analysis of these metrics by applying them to both synthetic and real-life sports data.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107049"},"PeriodicalIF":4.1000,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Operations Research","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0305054825000772","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

Abstract

The rankability of data is a novel problem that considers the ability of a dataset, represented as a graph, to produce a meaningful ranking of the items it contains. To study this concept, a number of rankability measures have been proposed, based on comparisons to a complete dominance graph via combinatorial and linear algebraic methods. Interest in this field has been steadily expanding, with a growing appreciation for the significance of evaluating rankability across diverse applications. Consequently, the validation of these rankability methodologies in different scenarios holds paramount importance. In this paper, we review existing measures of rankability and highlight some questions to which they give rise. We go on to introduce a new framework designed to evaluate rankability with a tailored approach, one that allows for efficient estimation in specific problem domains. Finally, we present a comparative analysis of these metrics by applying them to both synthetic and real-life sports data.
数据的可排序性是一个新问题,它考虑的是以图表示的数据集对其包含的项目进行有意义的排序的能力。为了研究这一概念,人们通过组合和线性代数方法,在与完整支配图进行比较的基础上,提出了许多可排序性测量方法。人们对这一领域的兴趣一直在稳步增长,对评估可排序性在各种应用中的重要性的认识也在不断提高。因此,在不同场景中验证这些可排序性方法至关重要。在本文中,我们回顾了现有的可排序性测量方法,并强调了这些方法所引发的一些问题。接着,我们将介绍一个新的框架,该框架旨在用一种量身定制的方法来评估可排序性,这种方法可以在特定问题领域中进行高效估算。最后,我们将这些指标应用于合成和真实的体育数据,并对其进行了比较分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Computers & Operations Research
Computers & Operations Research 工程技术-工程:工业
CiteScore
8.60
自引率
8.70%
发文量
292
审稿时长
8.5 months
期刊介绍: Operations research and computers meet in a large number of scientific fields, many of which are of vital current concern to our troubled society. These include, among others, ecology, transportation, safety, reliability, urban planning, economics, inventory control, investment strategy and logistics (including reverse logistics). Computers & Operations Research provides an international forum for the application of computers and operations research techniques to problems in these and related fields.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信