Rank aggregation methods dealing with incomplete information applied to smart cities

Dopazo González, Esther and Martínez Céspedes, María Luisa (2015). Rank aggregation methods dealing with incomplete information applied to smart cities. In: "International Conference on Fuzzy Systems (FUZZ-IEEE)", 02-05 Aug 2015, Estambul, Turkía. ISBN 978-1-4673-7428-6. pp. 1-7. https://doi.org/10.1109/FUZZ-IEEE.2015.7337965.

Description

Title: Rank aggregation methods dealing with incomplete information applied to smart cities
Author/s:
  • Dopazo González, Esther
  • Martínez Céspedes, María Luisa
Item Type: Presentation at Congress or Conference (Article)
Event Title: International Conference on Fuzzy Systems (FUZZ-IEEE)
Event Dates: 02-05 Aug 2015
Event Location: Estambul, Turkía
Title of Book: FUZZ-IEEE 2015: IEEE International Conference on Fuzzy Systems
Date: 2015
ISBN: 978-1-4673-7428-6
Volume: 1
Subjects:
Freetext Keywords: Rank Aggregation; Incomplete Information; Fuzzy Preference Relation; Smart City
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Lenguajes y Sistemas Informáticos e Ingeniería del Software
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

City-rankings have become a central instrument for assessing the attractiveness of urban regions over the last years. Demographic, environmental, economic, political and socio-cultural factors are forcing the urban world to design and implement Smart Cities. A set of multidimensional components underlies the fuzzy smart city concept. As a result cities are evaluated and ranked with regard to different characteristics, and smart city measures are achieved through chosen indicators. Therefore, the problem of combining multiple rankings to form an aggregate ranking, which compares city performance, is recognized as a useful tool in this context. Moreover, a usual situation is when incomplete information arises and only partial rankings may be supplied. This paper addresses the general problem of rank aggregation dealing with incomplete information based on rank aggregation methods and multicriteria decision making theory. It consists on constructing a consensus ranking from partial rankings of a set of objects provided according different criteria. Our techniques rely on outranking matrices as a way of collecting relevance information from input data, theory of fuzzy preference relations and the PageRank algorithm.

More information

Item ID: 45087
DC Identifier: http://oa.upm.es/45087/
OAI Identifier: oai:oa.upm.es:45087
DOI: 10.1109/FUZZ-IEEE.2015.7337965
Official URL: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7329077
Deposited by: Memoria Investigacion
Deposited on: 09 Mar 2017 13:04
Last Modified: 09 Mar 2017 13:04
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