R/movies.R

In CFilt: Collaborative Filtering by Reference Classes

#' Movie ratings by users
#'
#' A dataset containing 7276 ratings for 50 movies by 526 users. This database was created by Giglio (2014).
#'
#' @format A data frame with 7276 rows and 3 variables:
#' \describe{
#'   \item{Id Users}{Users identifier. Numbers 1 to 526. }
#'   \item{Id Items}{
#'   Movies identifier. Movies list:
#'  \enumerate{
#'    \item Iron Man 3
#'    \item Despicable Me 2
#'    \item My Mom Is a Character
#'    \item Fast & Furious 6
#'    \item The Wolverine
#'    \item Thor: The Dark World
#'    \item Hansel & Gretel: Witch Hunters
#'    \item Wreck-It Ralph
#'    \item Monsters University
#'    \item The Hangover Part III
#'    \item Vai Que Dá Certo
#'    \item Meu Passado me Condena
#'    \item We’re So Young
#'    \item Brazilian Western
#'    \item O Concurso
#'    \item Mato sem Cachorro
#'    \item Cine Holliudy
#'    \item Odeio o Dia dos Namorados
#'    \item Argo
#'    \item Django Unchained
#'    \item Life of Pi
#'    \item Lincoln
#'    \item Zero Dark Thirty
#'    \item Les Miserables
#'    \item Silver Linings Playbook
#'    \item Beasts of the Southern Wild
#'    \item Amour
#'    \item A Royal Affair
#'    \item American Hustle
#'    \item Capitain Phillips
#'    \item 12 Years a Slave
#'    \item Dallas Buyers Club
#'    \item Gravity
#'    \item Her
#'    \item Philomena
#'    \item The Wolf of Wall Street
#'    \item The Hunt
#'    \item Frozen
#'    \item Till Luck Do Us Part 2
#'    \item Muita Calma Nessa Hora 2
#'    \item Paranormal Activity: The Marked Ones
#'    \item I, Frankenstein,
#'    \item The Legend of Tarzan
#'    \item The Book Thief
#'    \item The Lego Movie, , ,
#'    \item Walking With Dinosaurs
#'    \item The Hunger Games: Catching Fire
#'    \item Blue Is The Warmest Color
#'    \item Reaching for the Moon
#'    \item The Hobbit: The Desolation of Smaug
#'    }
#'   }
#'   \item{Ratings}{Movie ratings by users. The ratings follows the Likert scale: 1 to 5.}
#' }
#'@references Giglio , J. C. (2014). Recomendação de Filmes Utilizando Filtragem Colaborativa [Recommending Films Using Collaborative Filtering]. Undergraduate thesis - Universidade Federal Fluminense.
"movies"