Detecting Tourist's Preferences by Sentiment Analysis in Smart Cities

摘要

Smart tourism is one of the significant areas of smart cities. One of the important tasks of smart tourism systems is to intelligently and automatically extract a user's preferences. This paper investigates the automatic extraction of users' preferences in smart tourism. To this end, users' comments published in social networks are exploited as a rich data source that implicitly includes their preferences. The proposed method extracts users' preferences through semantic clustering the comments and sentiment analysis. Evaluation results indicate high values of precision, recall, and f-measure parameters in tourist preference extraction.