User models for recommendation systems

Abstract

Currently, a user model or a representation of the user is used to recommend, personalize, predict, and manage inference in different recommender systems. Now, all the necessary user information is scattered. This document presents a systematic study to identify all the user information that recommendation systems use, represented or not by means of a model. This searching is important because it identifies the different data sources where user models are analyzed, and attributes and forms of user interaction are identified. The results presented are very useful for structuring a generalized user model.