Exploring content-based group recommendation for suggesting restaurants in Havana City
Recommender systems (RSs) are a relevant kind of artificial intelligence-based systems focused on providing users with the information that best fit their preferences and needs in a search space overloaded of possible options. Specifically, group recommender systems (GRSs) are a special type of RS c...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Graz University of Technology
2024-01-01
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| Series: | Journal of Universal Computer Science |
| Subjects: | |
| Online Access: | https://lib.jucs.org/article/104838/download/pdf/ |
| _version_ | 1797338709173993472 |
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| author | Yilena Pérez-Almaguer Edianny Carballo-Cruz Yailé Caballero-Mota Raciel Yera |
| author_facet | Yilena Pérez-Almaguer Edianny Carballo-Cruz Yailé Caballero-Mota Raciel Yera |
| author_sort | Yilena Pérez-Almaguer |
| collection | DOAJ |
| description | Recommender systems (RSs) are a relevant kind of artificial intelligence-based systems focused on providing users with the information that best fit their preferences and needs in a search space overloaded of possible options. Specifically, group recommender systems (GRSs) are a special type of RS centered on recommending items that are consumed in groups and not individually, being TV program and touristic packages key examples of such items. The current work is focused on proposing a content-based group recommendation approach (CB-GRS) contextualized to the restaurant recommendation domain. In contrast to previous content-based group recommendation models, the proposal incorporates novel stages such as restaurants feature imputation, the generation of a virtual group profile, the use of feature weighting, and the automatic selection of the most appropriate aggregation approach for composing group recommendations. The proposal is evaluated in an original recommendation scenario, related to restaurant from Havana City in Cuba, where several restaurant attributes are identified for applying the proposed CB-GRS approach. The experimental protocol evaluates individually each component of the proposal, evidencing their importance as part of the whole framework. Furthermore, the comparison with previous works has been also developed. The proposed approach can be applied in other recommendation scenarios, and in addition, the developed experimental protocol is generalizable for the evaluation of further content-based individual and group recommendation approaches in the tourism domain. |
| first_indexed | 2024-03-08T09:35:10Z |
| format | Article |
| id | doaj.art-c7bf48ac50d04068b252c2e7d567f5cf |
| institution | Directory Open Access Journal |
| issn | 0948-6968 |
| language | English |
| last_indexed | 2024-03-08T09:35:10Z |
| publishDate | 2024-01-01 |
| publisher | Graz University of Technology |
| record_format | Article |
| series | Journal of Universal Computer Science |
| spelling | doaj.art-c7bf48ac50d04068b252c2e7d567f5cf2024-01-30T10:45:28ZengGraz University of TechnologyJournal of Universal Computer Science0948-69682024-01-0130110612910.3897/jucs.104838104838Exploring content-based group recommendation for suggesting restaurants in Havana CityYilena Pérez-Almaguer0Edianny Carballo-Cruz1Yailé Caballero-Mota2Raciel Yera3University of HolguínUniversity of Ciego de ÁvilaUniversity of CamagüeyUniversity of Ciego de ÁvilaRecommender systems (RSs) are a relevant kind of artificial intelligence-based systems focused on providing users with the information that best fit their preferences and needs in a search space overloaded of possible options. Specifically, group recommender systems (GRSs) are a special type of RS centered on recommending items that are consumed in groups and not individually, being TV program and touristic packages key examples of such items. The current work is focused on proposing a content-based group recommendation approach (CB-GRS) contextualized to the restaurant recommendation domain. In contrast to previous content-based group recommendation models, the proposal incorporates novel stages such as restaurants feature imputation, the generation of a virtual group profile, the use of feature weighting, and the automatic selection of the most appropriate aggregation approach for composing group recommendations. The proposal is evaluated in an original recommendation scenario, related to restaurant from Havana City in Cuba, where several restaurant attributes are identified for applying the proposed CB-GRS approach. The experimental protocol evaluates individually each component of the proposal, evidencing their importance as part of the whole framework. Furthermore, the comparison with previous works has been also developed. The proposed approach can be applied in other recommendation scenarios, and in addition, the developed experimental protocol is generalizable for the evaluation of further content-based individual and group recommendation approaches in the tourism domain.https://lib.jucs.org/article/104838/download/pdf/content-based group recommendationrestaurant rec |
| spellingShingle | Yilena Pérez-Almaguer Edianny Carballo-Cruz Yailé Caballero-Mota Raciel Yera Exploring content-based group recommendation for suggesting restaurants in Havana City Journal of Universal Computer Science content-based group recommendation restaurant rec |
| title | Exploring content-based group recommendation for suggesting restaurants in Havana City |
| title_full | Exploring content-based group recommendation for suggesting restaurants in Havana City |
| title_fullStr | Exploring content-based group recommendation for suggesting restaurants in Havana City |
| title_full_unstemmed | Exploring content-based group recommendation for suggesting restaurants in Havana City |
| title_short | Exploring content-based group recommendation for suggesting restaurants in Havana City |
| title_sort | exploring content based group recommendation for suggesting restaurants in havana city |
| topic | content-based group recommendation restaurant rec |
| url | https://lib.jucs.org/article/104838/download/pdf/ |
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