A Review on Filtering Techniques used in Restaurant Recommendation System
T. Choenyi, T. Tseyang, S. Choikyong, P. Tsering, T. Gurme · International Journal of Computer Science and Mobile Computing · 2021
These days, recommendation systems are extremely common.Recommendation systems are used in suggesting personalized content and services.These are the following recommendation techniques described in this paper: collaborative-based filtering, Content-based filtering, demographic-based filtering, hybrid filtering, along with some applicational research.The paper points over some of the drawbacks and benefits of these techniques.And How with the use of Hybrid filtering these techniques are combined together to remove these individual drawbacks and improve effectiveness.Further with reviews of some research based on these techniques, this paper studies on restaurant recommendation system, mainly suggesting restaurant to the customer based on similar customer satisfaction rating.This model uses content-based filtering for suggesting.