| Version: | 0.2-0 |
| Date: | 2022-05-31 |
| Title: | Jester Dataset for 'recommenderlab' |
| Author: | Michael Hahsler |
| Maintainer: | Michael Hahsler <mhahsler@smu.edu> |
| Description: | Provides the Jester Dataset for package recommenderlab. |
| Depends: | R (≥ 3.5.0), recommenderlab (≥ 1.0.0) |
| URL: | https://github.com/mhahsler/recommenderlabJester |
| License: | GPL-2 |
| Copyright: | Freely available for research use when acknowledged with the following reference: Eigentaste: A Constant Time Collaborative Filtering Algorithm. Ken Goldberg, Theresa Roeder, Dhruv Gupta, and Chris Perkins. Information Retrieval, 4(2), 133-151. July 2001. |
| NeedsCompilation: | no |
| Packaged: | 2022-05-31 17:25:15 UTC; hahsler |
| Repository: | CRAN |
| Date/Publication: | 2022-05-31 17:50:02 UTC |
Jester Dataset
Description
The data set contains the anonymous ratings data from the Jester Online Joke Recommender System collected between April 1999 and May 2003.
Usage
data(Jester)Format
The format is: Formal class 'realRatingMatrix' [package "recommenderlab"]
Details
24983 x 100 rating matrix (24983 users and 100 jokes) with 1,810,455 ratings between -10.00 and +10.00. All selected users have rated 15 or more jokes.
The text for the jokes are also available as a character vector of length 100
in JesterJokes.
References
Ken Goldberg, Theresa Roeder, Dhruv Gupta, and Chris Perkins. "Eigentaste: A Constant Time Collaborative Filtering Algorithm." Information Retrieval, 4(2), 133-151. July 2001.
Examples
data(Jester)
Jester
hist(getRatings(Jester), main = "Distribution of ratings")
# what is the best joke? (highest average rating)
best <- which.max(colMeans(Jester))
cat(JesterJokes[best])