Project Overview
Online hotel searching is a formidable task due to the wealth of online information. A hotel recommender system based on sales records includes the user's preference relations among hotels. The basic premise of the research is that the selling records include the user's preference relations among hotels. The proposed Hotel Recommendation System will help tourists to search hotels and recommend the most suitable hotel regarding their requirements such as location, expected budget and number of guests, room type, and hotel’s activity. The proposed system recommends hotels based on the preferences of users when a user selects a hotel. In order to recommend the hotels, this identifies the user’s preference transition and makes recommendations based on them. Based on user preference the system recommends a hotel when a user selects a hotel. The main function of the recommender system predicts users’ preferences from the rating information, filters some items from massive information, and suggests candidate items for the user. The system makes recommendations to a user based on a hotel that a user selects on the system.
A hotel recommender is of great use for travelers. Here the application is developed to provide recommendations of hotels according to user’s preferences. It removes the burden on the user to decide which hotel is suitable for them. The project is developed for the user to save their time in searching on the web where tremendous information is available. Our application provides the user with a precise list of hotels. Here we developed the application using machine learning.