Year: 2025
Type: article
Abstract: Earlier we have seen a eloquent rise in the use of recommendation systems in many different businesses, including the entertainment and tourist sectors. This abstract explores the integration of machine learning algorithms to enhance personalized hotel recommendations. They can perform the function of information filters by processing essential data from a variety of networks to provide consumer ideas that are relevant to their needs. When choosing hotels in cities all over the globe, many visitors and travelers often depend on written reviews, numerical ratings, and specific areas of interest. User preferences have a big impact on hotel recommendations. The most effective recommendations may be made by recommendation systems by utilizing historical user preference data.To solve this problem, recommender systems have suggested content-based filtering methods.
Source: Journal of Neonatal Surgery
Authors: Gurijala Durga Sai Chathurya, Gudivada Lokesh
Institution: Vemu Institute of Technology
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4408922785