| Title |
Intelligent Recommendation Framework For Tourist Attractions Based On Data Mining Technology |
| ID_Doc |
32496 |
| Authors |
Liu L. |
| Year |
2020 |
| Published |
Proceedings - International Conference on Smart Electronics and Communication, ICOSEC 2020 |
| DOI |
http://dx.doi.org/10.1109/ICOSEC49089.2020.9215404 |
| Abstract |
Intelligent recommendation framework for tourist attractions based on data mining technology is designed and implemented in this paper. This paper aims to design a real-Time travel recommendation system that does not require prior knowledge and can meet multiple constraints. In the work of this paper, the knowledge graph is represented by a core network knowledge base formed by triads and the mutual links between triads. Such triples are rich in the entities and their attribute information. When receiving the user request, the attractions are scored through the attraction scoring mechanism and then recommend the itinerary through a multi-constraint-based path planning algorithm. The recommended routes are evaluated and re-ranked by considering the diversity of the recommended scenic spots in the system, and finally, the best travel route is recommended for the users. The experiment compared with the other latest methods have proven the performance of the proposed model that can provide efficient recommendations.. © 2020 IEEE. |
| Author Keywords |
Data mining; feature extraction; recommendation system; smart cities; tourist attractions |
