Web-based application for places recommender using machine learning / Farah Nurshaziela, Ruzita Ahmad and Shukor Sanim Mohd Fauzi

Information about places to visit can be found easily on the internet, however, the information available might be overwhelming and users may have to spend considerable time locating those places that are interesting to them. Hence, tourists nowadays are looking for a simpler way to look for places’ recommendation in a certain country that suits their taste. Therefore, the Web-Based Application for Places Recommender using Machine Learning is developed. This system is developed mainly using Streamlit, Pandas, SK-Learn, HTML and CSS and the data that is gathered is encoded using CountVectorizer and then using Cosine Similarity to recommend the places. Then the system is evaluated using User Acceptance Testing by 20 respondents and the results are then used to improve the system.