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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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. |
format | Online Article Text |
id | pubmed-8947558 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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