A Personalized Hybrid Restaurant Recommender System through Conversations
Abstract: Providing accurate information from restaurants to make a decision on where to eat is becoming increasingly difficult as the amount of information and the number of options increases. The system treats the selection of restaurants of interest as an interactive and conversational process, with recommendation systems researching the attributes of restaurants and responding to the user. It was tested on a sample of 100 users.
Keywords: Recommendation systems, artificial intelligence, machine learning
How to Cite?: Karina Gonzalez Herrera, Maria Luisa Cervantes Piedras, Alejandro Ramirez Ramos, Blanca Estela Pedroza Mendez, Eduardo Sanchez Lucero, "A Personalized Hybrid Restaurant Recommender System through Conversations", Volume 9 Issue 9, September 2020, International Journal of Science and Research (IJSR), Pages: 755-758, https://www.ijsr.net/getabstract.php?paperid=SR20910003916, DOI: https://dx.doi.org/10.21275/SR20910003916