Open AccessHotel Content-Based Recommendation System
Author(s) -
Kristian Wahyudi,
Johanes Latupapua,
Ritchie Chandra,
Abba Suganda Girsang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1485/1/012017
Subject(s) - recommender system , process (computing) , computer science , information retrieval , collaborative filtering , user generated content , world wide web , content (measure theory) , mathematics , social media , mathematical analysis , operating system
Content based recommendation system tries to recommend items similar to those a given user has likely in the past, whereas systems designed according to the collaborative recommendation paradigm identify users whose preferences are similar to those of the given user and recommend items they have liked. The proposed recommendation system is discussing about Data finitihotel recommendations for a place across U.S. The selected process for the recommendation is calculating the rating of hotel categories on the city. By calculating hotel categories from several city by combining two features namely categories and taken from the city of the selected hotelcategory as well. The result of process will be recommended hotel with highest ratingto the user.