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Lara, Ana Sofia (2024) Reinforcing Hotel Recommendation Systems through the implementation of Hybrid Modeling. Masters thesis, Dublin, National College of Ireland.
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Abstract
So far in 2024, 326 new hotels have been or are planned to be build across Europe. Nowadays choosing which Hotel to travel to is an overwhelming experience due to the multiple options available online, it is time consuming and tiring. Current studies in the implementation of emerging technologies specially machine learning algorithms have targeted the usefulness of recommendation systems for Travel and Tourism services such as Hotel Recommendations. Diverse papers have discussed this subject focusing on the development of hybrid recommendations, leaning to implement not only user-based recommendations but also content and context based ones. This research will focus on the integration of both collaborative filtering (CF) and content-based filtering (CBF) to produce hybrid recommendation that will not only take similar users into account but the item attributes to formulate patterns of suggestion. The findings positively concluded that hybrid recommendations are more likely to be more accurate than only CF or CBF models individually as well as maintaining a high identification of false positive outcomes.
| Item Type: | Thesis (Masters) |
|---|---|
| Supervisors: | Name Email Onwuegbuche, Faithful UNSPECIFIED |
| Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science H Social Sciences > HD Industries. Land use. Labor > Specific Industries > Hospitality Industry Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning |
| Divisions: | School of Computing > Master of Science in Artificial Intelligence for Business |
| Depositing User: | Ciara O'Brien |
| Date Deposited: | 02 Jul 2025 16:22 |
| Last Modified: | 02 Jul 2025 16:22 |
| URI: | https://norma.ncirl.ie/id/eprint/7992 |
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