TraveLink, an AI-driven travel itinerary mobile application
The impact of the COVID-19 pandemic on the Tourism sector has been detrimental with many businesses within the sector struggling to recover. This situation has led to Singapore’s local government bodies, tourists, businesses on the search for solutions to regrow the sector. In the age of technology-...
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| Formato: | Final Year Project (FYP) |
| Idioma: | English |
| Publicado em: |
Nanyang Technological University
2023
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| Acesso em linha: | https://hdl.handle.net/10356/165868 |
| _version_ | 1826120280047616000 |
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| author | Or, Yi Ning |
| author2 | Kong Wai-Kin Adams |
| author_facet | Kong Wai-Kin Adams Or, Yi Ning |
| author_sort | Or, Yi Ning |
| collection | NTU |
| description | The impact of the COVID-19 pandemic on the Tourism sector has been detrimental with many businesses within the sector struggling to recover. This situation has led to Singapore’s local government bodies, tourists, businesses on the search for solutions to regrow the sector. In the age of technology-driven software solutions, TraveLink provides a solution to bring Tourism in countries back alive, starting with Singapore. TraveLink is an itinerary recommendation mobile application that is powered by AI and data-driven technology. It consists of six core functionalities, including an authentication system, questionnaire, peer preference system, itinerary generation, feedback mechanism, and operations on existing itineraries. This report details the technical implementation of TraveLink and focuses on five core contributions made to its development. The first implementation involved data collection for all aspects of destination-related data required by the application. The second implementation involved data processing and cleaning, including the conversion of destination reviews into word embeddings using Word2Vec Embedding Algorithm and clustering of these word embeddings using Agglomerative Clustering. The third implementation focused on the generation of the activity score, which is a core component of the application and serves as the foundation for the recommendation system. This score is generated by combining clusters from the previous steps and destination reviews as inputs into the Random Forest Machine Learning Model. The fourth implementation involved the implementation of operations on existing itineraries on both the front and back-end of the application. Lastly, the report details the core aspects and functionalities of the mobile application user interface, which have been developed as part of the technical implementation. |
| first_indexed | 2024-10-01T05:13:57Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/165868 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:13:57Z |
| publishDate | 2023 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1658682023-04-14T15:37:18Z TraveLink, an AI-driven travel itinerary mobile application Or, Yi Ning Kong Wai-Kin Adams School of Computer Science and Engineering AdamsKong@ntu.edu.sg Engineering::Computer science and engineering::Software::Software engineering The impact of the COVID-19 pandemic on the Tourism sector has been detrimental with many businesses within the sector struggling to recover. This situation has led to Singapore’s local government bodies, tourists, businesses on the search for solutions to regrow the sector. In the age of technology-driven software solutions, TraveLink provides a solution to bring Tourism in countries back alive, starting with Singapore. TraveLink is an itinerary recommendation mobile application that is powered by AI and data-driven technology. It consists of six core functionalities, including an authentication system, questionnaire, peer preference system, itinerary generation, feedback mechanism, and operations on existing itineraries. This report details the technical implementation of TraveLink and focuses on five core contributions made to its development. The first implementation involved data collection for all aspects of destination-related data required by the application. The second implementation involved data processing and cleaning, including the conversion of destination reviews into word embeddings using Word2Vec Embedding Algorithm and clustering of these word embeddings using Agglomerative Clustering. The third implementation focused on the generation of the activity score, which is a core component of the application and serves as the foundation for the recommendation system. This score is generated by combining clusters from the previous steps and destination reviews as inputs into the Random Forest Machine Learning Model. The fourth implementation involved the implementation of operations on existing itineraries on both the front and back-end of the application. Lastly, the report details the core aspects and functionalities of the mobile application user interface, which have been developed as part of the technical implementation. Bachelor of Engineering (Computer Science) 2023-04-14T00:30:56Z 2023-04-14T00:30:56Z 2023 Final Year Project (FYP) Or, Y. N. (2023). TraveLink, an AI-driven travel itinerary mobile application. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/165868 https://hdl.handle.net/10356/165868 en SCSE22-0179 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Computer science and engineering::Software::Software engineering Or, Yi Ning TraveLink, an AI-driven travel itinerary mobile application |
| title | TraveLink, an AI-driven travel itinerary mobile application |
| title_full | TraveLink, an AI-driven travel itinerary mobile application |
| title_fullStr | TraveLink, an AI-driven travel itinerary mobile application |
| title_full_unstemmed | TraveLink, an AI-driven travel itinerary mobile application |
| title_short | TraveLink, an AI-driven travel itinerary mobile application |
| title_sort | travelink an ai driven travel itinerary mobile application |
| topic | Engineering::Computer science and engineering::Software::Software engineering |
| url | https://hdl.handle.net/10356/165868 |
| work_keys_str_mv | AT oryining travelinkanaidriventravelitinerarymobileapplication |