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| author | Chen Chao <crazyjvm@gmail.com> | 2014-02-19 22:06:35 -0800 |
|---|---|---|
| committer | Reynold Xin <rxin@apache.org> | 2014-02-19 22:06:35 -0800 |
| commit | f9b7d64a4e7dd03be672728335cb72df4be5dbf6 (patch) | |
| tree | ec832b0ccc843f483889aee32a7e0ae0bc801f8c /mllib | |
| parent | 7b012c93973201a1cbb4fc9a02e322152e5185a9 (diff) | |
| download | spark-f9b7d64a4e7dd03be672728335cb72df4be5dbf6.tar.gz spark-f9b7d64a4e7dd03be672728335cb72df4be5dbf6.tar.bz2 spark-f9b7d64a4e7dd03be672728335cb72df4be5dbf6.zip | |
MLLIB-24: url of "Collaborative Filtering for Implicit Feedback Datasets" in ALS is invalid now
url of "Collaborative Filtering for Implicit Feedback Datasets" is invalid now. A new url is provided. http://research.yahoo.com/files/HuKorenVolinsky-ICDM08.pdf
Author: Chen Chao <crazyjvm@gmail.com>
Closes #619 from CrazyJvm/master and squashes the following commits:
a0b54e4 [Chen Chao] change url to IEEE
9e0e9f0 [Chen Chao] correct spell mistale
fcfab5d [Chen Chao] wrap line to to fit within 100 chars
590d56e [Chen Chao] url error
Diffstat (limited to 'mllib')
| -rw-r--r-- | mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala b/mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala index a990e0fb01..a566464d97 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala @@ -81,7 +81,7 @@ case class Rating(val user: Int, val product: Int, val rating: Double) * * For implicit preference data, the algorithm used is based on * "Collaborative Filtering for Implicit Feedback Datasets", available at - * [[http://research.yahoo.com/pub/2433]], adapted for the blocked approach used here. + * [[http://dx.doi.org/10.1109/ICDM.2008.22]], adapted for the blocked approach used here. * * Essentially instead of finding the low-rank approximations to the rating matrix `R`, * this finds the approximations for a preference matrix `P` where the elements of `P` are 1 if |