文章基本信息

标题：Tourist Recommender Systems Based on Emotion Recognition—A Scientometric Review
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作者：Luz Santamaria-Granados ; Juan Francisco Mendoza-Moreno ; Gustavo Ramirez-Gonzalez 等
期刊名称：Future Internet
电子版ISSN：1999-5903
出版年度：2021
卷号：13
期号：1
页码：2
DOI：10.3390/fi13010002
出版社：MDPI Publishing
摘要：Recommendation systems have overcome the overload of irrelevant information by considering users’ preferences and emotional states in the fields of tourism, health, e-commerce, and entertainment. This article reviews the principal recommendation approach documents found in scientific databases (Elsevier’s Scopus and Clarivate Web of Science) through a scientometric analysis in ScientoPy. Research publications related to the recommenders of emotion-based tourism cover the last two decades. The review highlights the collection, processing, and feature extraction of data from sensors and wearables to detect emotions. The study proposes the thematic categories of recommendation systems, emotion recognition, wearable technology, and machine learning. This paper also presents the evolution, trend analysis, theoretical background, and algorithmic approaches used to implement recommenders. Finally, the discussion section provides guidelines for designing emotion-sensitive tourist recommenders.
关键词：tourist recommender system; emotion recognition; sentiment analysis; machine learning; deep learning; wearable device; physiological signals tourist recommender system ; emotion recognition ; sentiment analysis ; machine learning ; deep learning ; wearable device ; physiological signals