A Contextual Multi-armed Bandit Approach to Personalized Trip Itinerary Planning
With the rise in people’s mobility and the flourishing of global tourism in recent years, there has been a notable interest in personalized trip planning. Trip itinerary planning (TIP) refers to the process of organizing and scheduling various elements of a journey, such as transportation, accommodations and activities, into a coherent and efficient plan. This paper particularly focuses on route personalization through points of interests (POIs), taking into account aspects such as budget constraints, hotel selection, users’ preferred POI categories, the duration of the trip, and the overall route length. To address these considerations, we implement Contextual Multi-armed Bandits (CMAB), a robust methodology where the decision-making is influenced by additional contextual information such as constraints and requirements of each traveller. The effectiveness of the proposed approach is validated by comparing against a baseline model in terms of user satisfaction and the time required to generate results. This paper demonstrates the potential of CMAB in personalized itinerary planning.
Authors
- Alaa Khamis (ORCID: https://orcid.org/0000-0003-3008-835X)
- Tianyu Shi (ORCID: https://orcid.org/0009-0006-5274-1101)
- Mufeng Wang (ORCID: https://orcid.org/0000-0001-5706-8960)
- Jiarui Zhang (ORCID: https://orcid.org/0000-0003-4776-852X)
- Haowei Li (ORCID: https://orcid.org/0000-0002-2742-0078)
Institutions
- Applied Science Private University (JO)
- University of Toronto (CA)
- General Motors (Canada) (CA)
Publication Details
- Published
- 2024-09-16
- DOI
- https://doi.org/10.1109/sm63044.2024.10733530
- Citations
- 1
- Primary Topic
- Advanced Bandit Algorithms Research
- Type
- article
- Field-Weighted Citation Impact
- 0.49