A Real-Time Tourism Recommender System Using KNN and RBM Approach

• Published in: 2023 International Conference on Data Science, Agents & Artificial Intelligence (ICDSAAI) pp. 1 - 5
• Main Authors: Kishore Murugananda, G, Shiny Angel, T.S., Kumar, Senthil, Snehalatha, N, Shaphan Manipaul, S
• Format: Conference Proceeding
• Language: English
• Published: IEEE 21.12.2023
• Subjects: Collaborative and Content-based Filtering; Hybrid Recommender systems; Recommendation systems; Tourism based Recommender system; Traveling Recommender system
• DOI: 10.1109/ICDSAAI59313.2023.10452558

Tourism holds a pivotal position in the nation's economic landscape, serving as a major driving force and playing a crucial role in shaping the trajectory of the industry. The desire for travel has increased over the years, leading to a rise in the number of tourists. As a result, businesses on a global and local scale, as well as governments, invest heavily in the industry. Investments mainly focus on providing tourists with comprehensive tour and hotel packages. Despite government investments in the maintenance and promotion of tourist attractions, there is frequently insufficient focus on enhancing the overall tourist experience. To address this gap, we aim to implement an innovative real-time recommender system that goes beyond conventional information provision and offers recommendations based on user preferences. We recognize the evolving complexities and dynamics of recommender system environments and strive to adapt to the changing sources and diversity of information available at runtime.We aim to create a proficient touring recommender system with real-time capabilities, guaranteeing that visitors obtain prompt ideas that enhance their overall experience. The objective is to provide an all-encompassing suggestion framework that assists travelers in the first phase of choosing which nation to visit and thereafter offers a thorough guide for their whole holiday. We are dedicated to providing tourists with the best possible experience, aiming to eliminate the need for external assistance. Key features of the application encompass providing comprehensive information on accommodations, dining options, and attractions, utilizing the user's current location for a personalized experience. This information will be tailored based on factors such as budget, popularity, and other relevant characteristics. Additionally, we plan to implement a timetabled feature that assists tourists in planning their activities based on the duration of their stay. Real-time assistance will also be a prominent feature, ensuring that users have continuous support during their travel experiences. In essence, our mission is to redefine the tourism experience by combining real-time recommendations with a user-centric approach, empowering tourists to make informed decisions and enjoy a seamless and memorable journey.