MovieLens 1M movie ratings. Stable benchmark dataset. 1 million ratings from 6000 users on 4000 movies. Released 2/2003.
These files contain 1,000,209 anonymous ratings of approximately 3,900 movies
made by 6,040 MovieLens users who joined MovieLens in 2000.
Neither the University of Minnesota nor any of the researchers
involved can guarantee the correctness of the data, its suitability
for any particular purpose, or the validity of results based on the
use of the data set. The data set may be used for any research
purposes under the following conditions:
* The user may not state or imply any endorsement from the
University of Minnesota or the GroupLens Research Group.
* The user must acknowledge the use of the data set in
publications resulting from the use of the data set
(see below for citation information).
* The user may not redistribute the data without separate
* The user may not use this information for any commercial or
revenue-bearing purposes without first obtaining permission
from a faculty member of the GroupLens Research Project at the
University of Minnesota.
If you have any further questions or comments, please contact GroupLens
To acknowledge use of the dataset in publications, please cite the following
F. Maxwell Harper and Joseph A. Konstan. 2015. The MovieLens Datasets: History
and Context. ACM Transactions on Interactive Intelligent Systems (TiiS) 5, 4,
Article 19 (December 2015), 19 pages. DOI=http://dx.doi.org/10.1145/2827872
Thanks to Shyong Lam and Jon Herlocker for cleaning up and generating the data
FURTHER INFORMATION ABOUT THE GROUPLENS RESEARCH PROJECT
The GroupLens Research Project is a research group in the Department of
Computer Science and Engineering at the University of Minnesota. Members of
the GroupLens Research Project are involved in many research projects related
to the fields of information filtering, collaborative filtering, and
recommender systems. The project is lead by professors John Riedl and Joseph
Konstan. The project began to explore automated collaborative filtering in
1992, but is most well known for its world wide trial of an automated
collaborative filtering system for Usenet news in 1996. Since then the project
has expanded its scope to research overall information filtering solutions,
integrating in content-based methods as well as improving current collaborative
Further information on the GroupLens Research project, including research
publications, can be found at the following web site:
GroupLens Research currently operates a movie recommender based on
RATINGS FILE DESCRIPTION
All ratings are contained in the file "ratings.dat" and are in the
- UserIDs range between 1 and 6040
- MovieIDs range between 1 and 3952
- Ratings are made on a 5-star scale (whole-star ratings only)
- Timestamp is represented in seconds since the epoch as returned by time(2)
- Each user has at least 20 ratings
USERS FILE DESCRIPTION
User information is in the file "users.dat" and is in the following
All demographic information is provided voluntarily by the users and is
not checked for accuracy. Only users who have provided some demographic
information are included in this data set.
- Gender is denoted by a "M" for male and "F" for female
- Age is chosen from the following ranges:
* 1: "Under 18"
* 18: "18-24"
* 25: "25-34"
* 35: "35-44"
* 45: "45-49"
* 50: "50-55"
* 56: "56+"
- Occupation is chosen from the following choices:
* 0: "other" or not specified
* 1: "academic/educator"
* 2: "artist"
* 3: "clerical/admin"
* 4: "college/grad student"
* 5: "customer service"
* 6: "doctor/health care"
* 7: "executive/managerial"
* 8: "farmer"
* 9: "homemaker"
* 10: "K-12 student"
* 11: "lawyer"
* 12: "programmer"
* 13: "retired"
* 14: "sales/marketing"
* 15: "scientist"
* 16: "self-employed"
* 17: "technician/engineer"
* 18: "tradesman/craftsman"
* 19: "unemployed"
* 20: "writer"
MOVIES FILE DESCRIPTION
Movie information is in the file "movies.dat" and is in the following
- Titles are identical to titles provided by the IMDB (including
year of release)
- Genres are pipe-separated and are selected from the following genres:
- Some MovieIDs do not correspond to a movie due to accidental duplicate
entries and/or test entries
- Movies are mostly entered by hand, so errors and inconsistencies may exist