Open AccessA Novel Model for Explainable Hostel Recommender System Using Hybrid Filtering
Author(s) -
Shahzad Ahmed Khan
Publication year - 2021
Publication title -
lahore garrison university research journal of computer science and information technology
Language(s) - English
Resource type - Journals
eISSN - 2521-0122
pISSN - 2519-7991
DOI - 10.54692/lgurjcsit.2021.0502203
Subject(s) - recommender system , computer science , collaborative filtering , domain (mathematical analysis) , curse of dimensionality , information retrieval , artificial intelligence , mathematics , mathematical analysis
Recommender systems help humans in filtering and finding the right information from the enormous amount of data. Hostels are more famous than hotels for solo travelers, but no prior research related to recommender systems has been conducted in this domain. Hostels allow users to provide multi-criteria ratings and traditional recommender systems are not able to provide effective recommendations in case of multi-dimensionality i.e. contextual information and multi-criteriaratings. So, we have proposed a novel hybrid recommender system (SAFCHERS) that chooses the hostel's features for computation dynamically and provides explainable and better recommendations than the traditional recommender systems.