A novel group tour trip recommender model for personalized travel systems
Planning personalized travel itineraries for groups with diverse preferences is indeed challenging. This article proposes a novel group tour trip recommender model (GTTRM), which uses ant colony optimization (ACO) to optimize group satisfaction while minimizing conflicts between group members. Unlik...
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| Format: | Article |
| Language: | English |
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PeerJ Inc.
2025-01-01
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| Series: | PeerJ Computer Science |
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| Online Access: | https://peerj.com/articles/cs-2589.pdf |
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| _version_ | 1832594289219076096 |
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| author | Mohammed Alatiyyah |
| author_facet | Mohammed Alatiyyah |
| author_sort | Mohammed Alatiyyah |
| collection | DOAJ |
| description | Planning personalized travel itineraries for groups with diverse preferences is indeed challenging. This article proposes a novel group tour trip recommender model (GTTRM), which uses ant colony optimization (ACO) to optimize group satisfaction while minimizing conflicts between group members. Unlike existing models, the proposed GTTRM allows dynamic subgroup formation during the trip to handle conflicting preferences and provide tailored recommendations. Experimental results show that GTTRM significantly improves satisfaction levels for individual group members, outperforming state-of-the-art models in terms of both subgroup management and optimization efficiency. |
| format | Article |
| id | doaj-art-7202d1aaaea4444e8ae07b28948c4961 |
| institution | Kabale University |
| issn | 2376-5992 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ Computer Science |
| spelling | doaj-art-7202d1aaaea4444e8ae07b28948c49612025-01-19T15:05:15ZengPeerJ Inc.PeerJ Computer Science2376-59922025-01-0111e258910.7717/peerj-cs.2589A novel group tour trip recommender model for personalized travel systemsMohammed AlatiyyahPlanning personalized travel itineraries for groups with diverse preferences is indeed challenging. This article proposes a novel group tour trip recommender model (GTTRM), which uses ant colony optimization (ACO) to optimize group satisfaction while minimizing conflicts between group members. Unlike existing models, the proposed GTTRM allows dynamic subgroup formation during the trip to handle conflicting preferences and provide tailored recommendations. Experimental results show that GTTRM significantly improves satisfaction levels for individual group members, outperforming state-of-the-art models in terms of both subgroup management and optimization efficiency.https://peerj.com/articles/cs-2589.pdfAnt colony optimizationGroup recommender systemsGroup tour trip design problemPersonalized tour trips |
| spellingShingle | Mohammed Alatiyyah A novel group tour trip recommender model for personalized travel systems PeerJ Computer Science Ant colony optimization Group recommender systems Group tour trip design problem Personalized tour trips |
| title | A novel group tour trip recommender model for personalized travel systems |
| title_full | A novel group tour trip recommender model for personalized travel systems |
| title_fullStr | A novel group tour trip recommender model for personalized travel systems |
| title_full_unstemmed | A novel group tour trip recommender model for personalized travel systems |
| title_short | A novel group tour trip recommender model for personalized travel systems |
| title_sort | novel group tour trip recommender model for personalized travel systems |
| topic | Ant colony optimization Group recommender systems Group tour trip design problem Personalized tour trips |
| url | https://peerj.com/articles/cs-2589.pdf |
| work_keys_str_mv | AT mohammedalatiyyah anovelgrouptourtriprecommendermodelforpersonalizedtravelsystems AT mohammedalatiyyah novelgrouptourtriprecommendermodelforpersonalizedtravelsystems |