Abstract: Tourism is a rapidly growing industry, and with the rise of machine learning techniques, it is possible to make personalized tourist recommendations. Machine learning models can analyse a large amount of tourist data, including historical tourist trends, demographic information, user preferences. To develop a personalized tourist recommendation system, one approach is to use a combination of machine learning algorithms. The proposed system helps in guiding users with all the information regarding tourist places. In this paper the system also provides a personalized experience to tourists by taking into account their individual preferences. The proposed system helps user to give rating and reviews on the places they visited.

Keywords: Recommendation Web Application, Machine learning, Collaborative filtering algorithm, Content-based filtering, Knowledge-based filtering.

PDF | DOI: 10.17148/IJARCCE.2023.12522

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