| Revista: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000607864 |
| ISSN: | 1405-5546 |
| Autores: | Cowlessur, Sanjeev K.1 Basava, Annappa2 Pati, Bibudhendu3 |
| Instituciones: | 1Universite des Mascareignes, Pamplemousses. Mauricio 2National Institute of Technology Karnataka, Surathkal. India 3Rama Devi Women’s University, Bhubaneswar. India |
| Año: | 2024 |
| Periodo: | Ene-Mar |
| Volumen: | 28 |
| Número: | 1 |
| Paginación: | 179-188 |
| País: | México |
| Idioma: | Inglés |
| Resumen en inglés | Over the past decades, tourism has become a key economic industry for many countries. In today’s global economy, it is an essential source of employment and revenue. Tourism as a leisure activity is a very popular form of recreation which involves the movement of people to foreign cities to visit new and unfamiliar places of interest (POIs). The task of recommending personalised tours for tourists is very demanding and time-consuming. The recommended tours must satisfy the tourist’s interests and must at the same time be completed within a limited time span and within some budget. In existing itinerary recommender systems, if there is no past visit history about a particular POI, then that POI is not included in the recommended itinerary. To address this challenge, we have devised an algorithm called PIONEER which is based on a genetic algorithm for suggesting an itinerary based on tourist interests, POI popularity, and travel costs. Our algorithm recommends itineraries for tourists who want to visit locations which are unfamiliar to them. We have used the publicly available Flickr dataset in our work. The results demonstrate the superiority of our PIONEER algorithm compared to the baseline algorithms with regards to metrics like precision, recall and F1-Score. |
| Keyword: | POI, Tour recommendation, NSGA-II, Multi-objective optimisation |
| Texto completo: | Texto completo (Ver PDF) Texto completo (Ver HTML) |
