ExploreLah: Personalised and smart trip planner for mobile tourism

• Main Authors: GUNAWAN, Aldy, HOE, Siu Loon, LIM, Xun Yi, TRAN, Linh Chi, NGUYEN, Dang Viet Anh
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: Algorithm; Point of interests; Recommender system; Trip planner; Artificial Intelligence and Robotics; Tourism and Travel
• Online Access: https://ink.library.smu.edu.sg/sis_research/8490; https://ink.library.smu.edu.sg/context/sis_research/article/9493/viewcontent/IEEM_2023___final_version__1_.pdf
• Institution: Singapore Management University

Various recommender systems for mobile tourism have been developed over the years. However, most of these recommender systems tend to overwhelm users with too much information and may not be personalised to user preferences. In this paper, we introduce ExploreLah, a personalised and smart trip planner for exploring Point of Interests (POIs) in Singapore. The user preferences are categorised into five groups: shopping, art & culture, outdoor activity, adventure, and nightlife. The problem is considered as the Team Orienteering Problem with Time Windows. The algorithm is developed to generate itineraries. Simulated experiments using test cases were performed to evaluate and validate the usability of the current version.