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A genetic-based pairwise trip planner recommender system
The massive growth of internet users nowadays can be a big opportunity for the businesses to promote their services. This opportunity is not only for e-commerce, but also for other e-services, such as e-tourism. In this paper, we propose an approach of personalized recommender system with pairwise p...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8164892/ https://www.ncbi.nlm.nih.gov/pubmed/34094811 http://dx.doi.org/10.1186/s40537-021-00470-6 |
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author | Qomariyah, Nunung Nurul Kazakov, Dimitar |
author_facet | Qomariyah, Nunung Nurul Kazakov, Dimitar |
author_sort | Qomariyah, Nunung Nurul |
collection | PubMed |
description | The massive growth of internet users nowadays can be a big opportunity for the businesses to promote their services. This opportunity is not only for e-commerce, but also for other e-services, such as e-tourism. In this paper, we propose an approach of personalized recommender system with pairwise preference elicitation for the e-tourism domain area. We used a combination of Genetic Agorithm with pairwise user preference elicitation approach. The advantages of pairwise preference elicitation method, as opposed to the pointwise method, have been shown in many studies, including to reduce incosistency and confusion of a rating number. We also performed a user evaluation study by inviting 24 participants to examine the proposed system and publish the POIs dataset which contains 201 attractions used in this study. |
format | Online Article Text |
id | pubmed-8164892 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-81648922021-06-01 A genetic-based pairwise trip planner recommender system Qomariyah, Nunung Nurul Kazakov, Dimitar J Big Data Research The massive growth of internet users nowadays can be a big opportunity for the businesses to promote their services. This opportunity is not only for e-commerce, but also for other e-services, such as e-tourism. In this paper, we propose an approach of personalized recommender system with pairwise preference elicitation for the e-tourism domain area. We used a combination of Genetic Agorithm with pairwise user preference elicitation approach. The advantages of pairwise preference elicitation method, as opposed to the pointwise method, have been shown in many studies, including to reduce incosistency and confusion of a rating number. We also performed a user evaluation study by inviting 24 participants to examine the proposed system and publish the POIs dataset which contains 201 attractions used in this study. Springer International Publishing 2021-05-30 2021 /pmc/articles/PMC8164892/ /pubmed/34094811 http://dx.doi.org/10.1186/s40537-021-00470-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Qomariyah, Nunung Nurul Kazakov, Dimitar A genetic-based pairwise trip planner recommender system |
title | A genetic-based pairwise trip planner recommender system |
title_full | A genetic-based pairwise trip planner recommender system |
title_fullStr | A genetic-based pairwise trip planner recommender system |
title_full_unstemmed | A genetic-based pairwise trip planner recommender system |
title_short | A genetic-based pairwise trip planner recommender system |
title_sort | genetic-based pairwise trip planner recommender system |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8164892/ https://www.ncbi.nlm.nih.gov/pubmed/34094811 http://dx.doi.org/10.1186/s40537-021-00470-6 |
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