Comparative Study on Natural Language Processing for Tourism Suggestion System

Nowadays, due to a large amount of tourism information such as attractions or activities, it is difficult for users to decide where to go or do specific activities without getting suggestions from experts, books, websites, etc. To support users wisely in choosing tourism activities, a recommendation or suggestion system using Natural Language Processing (NLP), which is a subdomain of Artificial Intelligence (AI), is proposed. NLP plays an important part in the pre-processing task of the recommender system to enhance the performance of the suggested output. This paper explores and compares the NLP techniques that are currently applied to the existing recommendation systems. Challenges and trends using NLP for suggestion systems in tourism are discussed.