Design of recommendation system for tourist spot using sentiment analysis based on CNN-LSTM

Sentiment analysis techniques used on texts play an important role in many fields including decision making systems. A variety of research has been actively conducted on sentiment analysis techniques such as an approach using word frequency or morphological analysis, and the method of using a complex neural network. In this paper, we apply sentiment analysis technology using a deep neural network to sightseeing reviews, add ratings to reviews which had not included them, supplement data to enable various classification by weather or season, and design a system that enables custom recommendations based on data. Finally, we examine the contextual features of tourist attractions and design an efficient pre-processing procedure based on the results, and describe the overall process such as building a suitable learning environment, combining review and weather information, and final recommendation method.