AI-POWERED RECOMMENDATION SYSTEMS FOR TRIP PLANNING

Abstract

Trip planning can be difficult due to the overwhelming amount of information available and the time-consuming process of finding the best deals on flights, accommodation, and activities, making it hard for individuals to make informed decisions and plan an itinerary efficiently. This survey paper's goal is to explore how artificial intelligence is used in web applications for trip planning. The paper will conduct a comprehensive review of existing approaches and technologies for trip planning and will evaluate the use of natural language processing and the GPT-3 language model in generating personalized itineraries. The survey will also examine the integration of flight and accommodation booking APIs in trip planning web applications and the impact on user satisfaction and efficiency. The results of this survey will provide valuable insights into the current state of the field and will help to inform the development of future trip planning web applications that use artificial intelligence to provide a more efficient and enjoyable trip planning experience for users.