A Novel Recommendation System for Tourist Places and its Speciality

By tremendous extension of Internet, information is the most important forms of tourism Big Data. The powerful way to express tourist thinking, text mining information has great capability to stimulate innovation in tourism professionals. Over the past decades, various text mining methods are proposed and implemented in tourism to enhance value describing techniques, construct tourism proposal models, generate tourism profiles, and establish process to monitor tourist's markets. The success of these technologies has been accelerated by advances in Natural Language Processing (NLP), ML, and DL. Understanding the complexities by these different approaches and tourism information sources, this analysis explores text mining methods which has been implemented to recent tourism big data analysis and tries to provide an up-to-date overview. Various data analyzing designs, content-based NLP methods of topic removal, text categorization, description of emotions, text clustering related to tourists' text mining and requests in tourism profiles, picture description of travel destinations, market requests, etc. The upcoming years will provide development rules for new tourism big data applications.