movies {CFilt}

Movie ratings by users

Description

A dataset containing 7276 ratings for 50 movies by 526 users. This database was created by Giglio (2014).

Usage

movies

Format

A data frame with 7276 rows and 3 variables:

Id Users

Users identifier. Numbers 1 to 526.

Id Items

Movies identifier. Movies list:

1. Iron Man 3

2. Despicable Me 2

3. My Mom Is a Character

4. Fast & Furious 6

5. The Wolverine

6. Thor: The Dark World

7. Hansel & Gretel: Witch Hunters

8. Wreck-It Ralph

9. Monsters University

10. The Hangover Part III

11. Vai Que Dá Certo

12. Meu Passado me Condena

13. We’re So Young

14. Brazilian Western

15. O Concurso

16. Mato sem Cachorro

17. Cine Holliudy

18. Odeio o Dia dos Namorados

19. Argo

20. Django Unchained

21. Life of Pi

22. Lincoln

23. Zero Dark Thirty

24. Les Miserables

25. Silver Linings Playbook

26. Beasts of the Southern Wild

27. Amour

28. A Royal Affair

29. American Hustle

30. Capitain Phillips

31. 12 Years a Slave

32. Dallas Buyers Club

33. Gravity

34. Her

35. Philomena

36. The Wolf of Wall Street

37. The Hunt

38. Frozen

39. Till Luck Do Us Part 2

40. Muita Calma Nessa Hora 2

41. Paranormal Activity: The Marked Ones

42. I, Frankenstein,

43. The Legend of Tarzan

44. The Book Thief

45. The Lego Movie, , ,

46. Walking With Dinosaurs

47. The Hunger Games: Catching Fire

48. Blue Is The Warmest Color

49. Reaching for the Moon

50. The Hobbit: The Desolation of Smaug

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.