A Study of Neural Network Learning-Based Recommender System
Sumi Shin · The International Journal of Engineering and Science · 2017
A recommender system sorts and recommends the information which meets personal preferences among a huge amount of data provided by e-commerce.In particular, collaborative filtering (CF) is the most widely used technique in these recommendation systems.This method finds neighboring users who have similar preferences with particular users and recommends the items preferred by the former.This study proposes a neural network learning model as a new technique to find neighboring users using the collaborative filtering method.This kind of neural network learning model takes care of a sparseness problem during the analysis stage among those related with target users.The proposed method was tested with MovieLens data sets, and the results showed that precision improved by 6.7%.