Neural Collaborative Filtering Classification Model to Obtain Prediction Reliabilities

• DOI: 10.9781/ijimai.2021.08.010
• Publication Date: 2021-08-31T13:32:03Z
• Authors: Jesús Bobadilla; Abraham Gutiérrez; Santiago Alonso; Ángel González-Pr...
• Keywords: FOS: Computer and information sciences; Technology; neural classification; neural collaborative filtering; recommendation systems; T; 0202 electrical engineering, electronic engineering, information engineering; IJIMAI; 02 engineering and technology; artificial intelligence; Information Retrieval (cs.IR); Computer Science - Information Retrieval

Neural collaborative filtering is the state of art field in recommender systems area; it provides some models that obtain accurate predictions and recommendations. These are regression-based, they just return rating predictions. This paper proposes use a classification-based approach, returning both their reliabilities. The extra information (prediction reliabilities) can be used variety relevant areas such as detection shilling attacks, recommendations explanation or navigational tools to show users items dependences. Additionally, recommendation reliabilities gracefully provided users: "probably you will like this film", "almost certainly song", etc. proposed neural architecture; also tests quality its results good baselines. Remarkably, individual improved by using architecture compared Experiments have been performed making four popular public datasets, showing generalizable results. Overall, improves quality, maintains opens doors set fields.