Biclustering ARTMAP collaborative filtering recommender system

Autor: Ashraf M. Abdelbar, Donald C. Wunsch, Islam Elnabarawy
Rok vydání: 2016
Předmět:
Zdroj: IJCNN
DOI: 10.1109/ijcnn.2016.7727578
Popis: Collaborative filtering provides recommendations based on the behavior of each user combined with behavior of users with similar interests. Recommender systems are becoming widespread, helping people choose movies, books, and things to buy. In this study, we examine the use of Biclustering ARTMAP to build a collaborative filtering recommendation system. We introduce a novel modification to how the Biclustering ARTMAP algorithm computes the item-cluster similarity, and a way to adapt it for the prediction of user ratings. We apply the algorithm to the MovieLens 100k dataset, and find that it achieves promising performance compared to other collaborative filtering techniques.
Databáze: OpenAIRE