#mymedialite

[zenoga]

Cool.

A recommendation system prototype by BBC, based on the Java version of MyMediaLite. As far as I understand the blog post, an attribute-based model is computed on the server.

The actual recommendations are then computed on the client side, so that no user data is transferred to the server.

[zenoga]

Now that Lucene.Net graduated from the Apache Incubator, why not use it for MyMediaLite?

Any volunteers?

[zenoga]

Evaluation script for KDD Cup 2012, track 1

The KDD Cup 2012 has recently started, and there are already more than 200 participating teams. This year, the competition is hosted by Kaggle.

Because there were several questions in the forum about the evaluation measure MAP@3, I hereby publish my validation script, hoping that it may be useful.

The script expects two files, one prediction file and one file containing the ground truth (actual clicks). The prediction file is similar to the submission file format - the only exception is that it should contain exactly one recommendation list per user. The ground truth file is a "standard" rating file, just like rec_log_test.txt and rec_log_train.txt.

How to call the script:

./evaluate.pl --prediction-file=pred --groundtruth-file=rec_log_train.last0.1.txt

I created the file rec_log_train.last0.1.txt using the command

tail -n 7320927 rec_log_train.txt > reg_log_train.last0.1.txt

The script is written Perl, which should be installed by default on a typical Linux or Mac OS X machine. You can download it from GitHub: https://github.com/zenogantner/MyMediaLite/blob/master/scripts/kddcup2012/evaluate.pl

Of course, I cannot guarantee that it works correctly. If you have questions or suggestions for improvement, do not hesitate to contact me.

[zenoga]

[zenoga]

Today I learned ...

... some new things about git: How to push things to remote branches, and how to push things to several remote repositories at once (thanks to Carsten for the hint).

Remote Branches

Currently, I am re-working some underlying data structures of MyMediaLite, the recommender system library that I (well, mostly me) develop. This breaks things BIG TIME, and for quite a while. In other words, a really good case for branching.

I knew how local branching and merging works, but I had no idea how to push the contents of branches to a remote repository without pushing it to the remote master branch.

It turns out it is quite easy:

git push [email protected]:mymedialite/mymedialite.git new_ratings:new_ratings

Well, everything looks easy with git once you find out how to do it. It was not obvious to me, and reading the man pages also did not really help.

Pushing to Several Remote Repositories

My other problem was that I wanted to keep both the gitorious as well as the github repository up to date. StackOverflow had the answer. This is how it looks in my .gitconfig file:

[remote "MML"] url = [email protected]:mymedialite/mymedialite.git url = [email protected]:zenogantner/MyMediaLite.git

I can then use the MML alias to push to both repositories:

git push MML

Combining Both Features

And guess what, of course the two features can be combined without a problem:

git push MML new_ratings:new_ratings

[zenoga]

Free CeBIT Tickets

Next week. we will present some of our research (including the MyMediaLite recommender system library) at CeBIT in Hannover. CeBIT is Germany's biggest computer trade show.

Visit us in hall 9 at booth 24. We still have some remaining free tickets, if you are interested just send an e-mail to [email protected].

Some links with further information:

http://ismll.de/aktuelles/index_en.html

http://www.mymediaproject.org

http://ismll.de/mymedialite

[zenoga]

MyMediaLite: New Release & Download Statistics

We have released version 0.09 of our recommender system library MyMediaLite this week.

The most notable changes are support for reading data from SQL databases (and other data sources supporting the IDataReader interface), the addition of the Slope One rating prediction engine, and initial support for cross-validation.

I am also happy to announce that there already have been more than 700 downloads of MyMediaLite over the last three and a half months. While 700 may not sound much, I think it is not too bad for a niche product like MyMediaLite.

Additionally, the download count on mloss.org has exceeded 280, and more than 1500 people have viewed MyMediaLite's description there.

[zenoga]

Porting MyMediaLite to Java: First Steps

One of the most frequently heard complaints about our MyMediaLite recommender system library is that it is not written in Java. It seems that many recommender systems researchers and practitioners use Java as their preferred platform.

So I was thinking about a Java port of MyMediaLite for a while now, and I was very happy to find a student willing to do the port as a semester project.

Andreas (the student in charge of the Java port) has ported the first rating prediction engine to Java, and it delivers the same results as the C# implementation ;-).

It is not yet as fast as the C# version of MyMediaLite (C# handles scenarios with many objects much nicer than Java ...), but we will work on that, too.

Great job so far, Andreas!