View Proposal

---

Proposer

Chee Een Yap

Title

Development of a Tourism Spot Recommendation System with Zero-Shot Learning

Goal

To develop a Zero-Shot Learning-based tourism spot recommendation system that generates personalized travel recommendations by matching user preferences with semantic descriptions of tourist attractions, including previously unseen destinations.

Description

Traditional recommendation systems often rely on historical user interactions and large labelled datasets, which may limit their ability to recommend newly added or less popular tourist attractions. This project aims to develop a Zero-Shot Learning (ZSL)-Based Tourism Spot Recommendation System that provides personalized travel recommendations based on user preferences, travel objectives, budget, and contextual information. By leveraging Zero-Shot Learning techniques, the system can recommend tourism spots that have not been explicitly included in the training dataset by utilizing semantic descriptions and relationships between attractions and user interests. The proposed system will collect information such as preferred activities, destination types, budget range, travel duration, and travel companions. By using Zero-Shot Learning, the recommendation engine will match user profiles with tourism spot descriptions to generate personalized suggestions. Additional contextual factors such as weather conditions, distance, popularity ratings, and seasonal suitability may also be incorporated to improve recommendation quality.

Resources

Background

Url

Difficulty Level

Easy

Ethical Approval

None

Number Of Students

1

Supervisor

Chee Een Yap

Keywords

zero-shot learning, tourism spot recommendation

Degrees

Bachelor of Science in Computing Science