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Analysis of ranking data
Author(s) -
Yu Philip L. H.,
Gu Jiaqi,
Xu Hang
Publication year - 2019
Publication title -
wiley interdisciplinary reviews: computational statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.693
H-Index - 38
eISSN - 1939-0068
pISSN - 1939-5108
DOI - 10.1002/wics.1483
Subject(s) - ranking (information retrieval) , nonparametric statistics , rank (graph theory) , computer science , data set , preference , set (abstract data type) , information retrieval , statistical analysis , data mining , statistics , data science , mathematics , artificial intelligence , combinatorics , programming language
Ranking is one of the simple and efficient data collection techniques to understand individuals' perception and preferences for some items such as products, people, and species. Ranking data are frequently collected when individuals are asked to rank a set of items according to a certain preference criterion. Over the years, many statistical models and methods have been developed for analyzing ranking data. This paper will give a literature review of these models and methods and present the recent advances of the analysis of ranking data. This article is categorized under: Statistical and Graphical Methods of Data Analysis > Nonparametric Methods