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A TOPSIS-Inspired Ranking Method Using Constrained Crowd Opinions for Urban Planning

Crowdsourcing has become an important tool for gathering knowledge for urban planning problems. The questions posted to the crowd for urban planning problems are quite different from the traditional crowdsourcing models. Unlike the traditional crowdsourcing models, due to the constraints among the m...

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Detalles Bibliográficos
Autores principales: Chatterjee, Sujoy, Lim, Sunghoon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8947558/
https://www.ncbi.nlm.nih.gov/pubmed/35327882
http://dx.doi.org/10.3390/e24030371
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author Chatterjee, Sujoy
Lim, Sunghoon
author_facet Chatterjee, Sujoy
Lim, Sunghoon
author_sort Chatterjee, Sujoy
collection PubMed
description Crowdsourcing has become an important tool for gathering knowledge for urban planning problems. The questions posted to the crowd for urban planning problems are quite different from the traditional crowdsourcing models. Unlike the traditional crowdsourcing models, due to the constraints among the multiple components (e.g., multiple locations of facilities) in a single question and non-availability of the defined option sets, aggregating of multiple diverse opinions that satisfy the constraints as well as finding the ranking of the crowd workers becomes challenging. Moreover, owing to the presence of the conflicting nature of features, the traditional ranking methods such as the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) cannot always be feasible as the optimal solutions in terms of multiple objectives cannot occur simultaneously for the conflicting cases (e.g., benefit and cost criteria) for urban planning problems. Therefore, in this work, a multi-objective approach is proposed to produce better compromised solutions in terms of conflicting features from the general crowd. In addition, the solutions are employed to obtain a proper ideal solution for ranking the crowd. The experimental results are validated using two constrained crowd opinion datasets for real-world urban planning problems and compared with the state-of-the-art TOPSIS models.
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spelling pubmed-89475582022-03-25 A TOPSIS-Inspired Ranking Method Using Constrained Crowd Opinions for Urban Planning Chatterjee, Sujoy Lim, Sunghoon Entropy (Basel) Article Crowdsourcing has become an important tool for gathering knowledge for urban planning problems. The questions posted to the crowd for urban planning problems are quite different from the traditional crowdsourcing models. Unlike the traditional crowdsourcing models, due to the constraints among the multiple components (e.g., multiple locations of facilities) in a single question and non-availability of the defined option sets, aggregating of multiple diverse opinions that satisfy the constraints as well as finding the ranking of the crowd workers becomes challenging. Moreover, owing to the presence of the conflicting nature of features, the traditional ranking methods such as the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) cannot always be feasible as the optimal solutions in terms of multiple objectives cannot occur simultaneously for the conflicting cases (e.g., benefit and cost criteria) for urban planning problems. Therefore, in this work, a multi-objective approach is proposed to produce better compromised solutions in terms of conflicting features from the general crowd. In addition, the solutions are employed to obtain a proper ideal solution for ranking the crowd. The experimental results are validated using two constrained crowd opinion datasets for real-world urban planning problems and compared with the state-of-the-art TOPSIS models. MDPI 2022-03-05 /pmc/articles/PMC8947558/ /pubmed/35327882 http://dx.doi.org/10.3390/e24030371 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chatterjee, Sujoy
Lim, Sunghoon
A TOPSIS-Inspired Ranking Method Using Constrained Crowd Opinions for Urban Planning
title A TOPSIS-Inspired Ranking Method Using Constrained Crowd Opinions for Urban Planning
title_full A TOPSIS-Inspired Ranking Method Using Constrained Crowd Opinions for Urban Planning
title_fullStr A TOPSIS-Inspired Ranking Method Using Constrained Crowd Opinions for Urban Planning
title_full_unstemmed A TOPSIS-Inspired Ranking Method Using Constrained Crowd Opinions for Urban Planning
title_short A TOPSIS-Inspired Ranking Method Using Constrained Crowd Opinions for Urban Planning
title_sort topsis-inspired ranking method using constrained crowd opinions for urban planning
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8947558/
https://www.ncbi.nlm.nih.gov/pubmed/35327882
http://dx.doi.org/10.3390/e24030371
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