en http://creativecommons.org/licenses/by-nc-sa/2.0/uk/ Thu, 1 Jan 1970 00:00:00 +0000 Thu, 1 Jan 1970 00:00:00 +0000 60 http://www.audioscrobbler.net/data/webservices http://www.last.fm/group/Playground/journal The Last.fm group journal for Playground. Last.fm journals are a place to talk about all things music. http://www.last.fm/user/evilrix/journal/2010/06/01/3of03n_accidentally_deleted_an_artist_or_track%3F_read_this... Tue, 1 Jun 2010 06:52:55 +0000 http://www.last.fm/user/evilrix/journal/2010/06/01/3of03n_accidentally_deleted_an_artist_or_track%3F_read_this... All,

We'd like to announce a small tool we've written for the playground that allows you to restore any artist or track you may have deleted from your library by accident.

It's not all bells and whistles, but it might be useful if you've ever removed something from your library only to have that gut wrenching feeling when you realize you've deleted more that you intended.

Here is the blog post announcing it formally.
http://blog.last.fm/2010/06/01/now-in-the-playground-restore-artist-tracks

Hopefully you'll find this useful but if you do find any issues of have any feedback please do let us know by posting on the blog.

All the best.

-evilrix]]> http://www.last.fm/user/evilrix/journal/2010/06/01/3of03n_accidentally_deleted_an_artist_or_track%3F_read_this...#comments http://www.last.fm/user/E1i45/journal/2009/10/13/32yv1d_new_toys Tue, 13 Oct 2009 16:39:17 +0000 http://www.last.fm/user/E1i45/journal/2009/10/13/32yv1d_new_toys In praise of our loyal subscribers we've added a subscriber only VIP zone to playground with some new toys. We'll be adding more to our VIP area in the future. As usual we'd love to hear your feedback as it helps shape the future of Last.fm.

The new demonstrations are:

Image Charts
Creates a collage of artist images where the size corresponds to how often you've been listening to the artist. You can adjust the time frame from when your scrobbles are counted and other settings.

History Charts
Graphs for your top artists showing how often and when you listened to them.

Artist Connections
Ever wondered how Paris Hilton is connected to Metallica? Find out how artists are connected through the similar artists network.]]> http://www.last.fm/user/E1i45/journal/2009/10/13/32yv1d_new_toys#comments http://www.last.fm/user/klbostee/journal/2008/10/23/28joys_some_%22multi_tag_search%22_stats Thu, 23 Oct 2008 08:30:24 +0000 http://www.last.fm/user/klbostee/journal/2008/10/23/28joys_some_%22multi_tag_search%22_stats The "Multi Tag Search" has been on Playground since day one, but still lots of people seem to be using it. We keep receiving new queries every day, adding up to not much less than 20 thousand unique queries so far. Here are a few clever examples:

* beautiful guitar instrumental
* acoustic atmospheric melancholic
* hilarious cover
* "one hit wonder" 90s
* american "guilty pleasure"

A quick and dirty classification of the 250 most frequently occurring tags revealed that:

* 51% are genres (e.g. rock, pop)
* 26% are styles (e.g. experimental)
* 7% are locales (e.g. british, detroit)
* 5% are instruments (e.g. piano, guitar)
* 4% are moods (e.g. sad, romantic)
* 3% are times (e.g. 90s, oldies)
* 2% are opinions (e.g. beautiful, love)

The remaining 2% are tags like free and cover. Together with the many e-mails and forum posts, this led to a way bigger pile of feedback than what we were hoping for. You guys really did an amazing job! We learned a lot from it, and we are definitely planning to take this knowledge into account.

If you're interested in this stuff, you might want to have a look at this
poster by the way. We used it as wall decoration during our demo about the "Multi Tag Search" at ISMIR, a conference where researchers who work with music-related data meet. Elias also teamed up with Paul from Sun Labs to give an awesome tutorial about social tags at this conference, and he participated in the interesting panel on "Commercial Music Discovery and Recommendation" as well.]]> http://www.last.fm/user/klbostee/journal/2008/10/23/28joys_some_%22multi_tag_search%22_stats#comments http://www.last.fm/user/klbostee/journal/2008/07/30/23d42r_user-to-user_recommendations_charts Wed, 30 Jul 2008 07:14:43 +0000 http://www.last.fm/user/klbostee/journal/2008/07/30/23d42r_user-to-user_recommendations_charts It's time to announce the first Playground casualty. We actually liked this demo a lot, but you guys seemed to disagree since it has consistently been the least popular demo for a while now. However, we're really just making place for new demos to come by removing this one, so stay tuned!]]> http://www.last.fm/user/klbostee/journal/2008/07/30/23d42r_user-to-user_recommendations_charts#comments http://www.last.fm/user/klbostee/journal/2008/06/19/215mec_multi_tag_search_igoogle_gadget Thu, 19 Jun 2008 15:31:33 +0000 http://www.last.fm/user/klbostee/journal/2008/06/19/215mec_multi_tag_search_igoogle_gadget Go get it!]]> http://www.last.fm/user/klbostee/journal/2008/06/19/215mec_multi_tag_search_igoogle_gadget#comments http://www.last.fm/user/klbostee/journal/2008/06/05/20epfr_most_unwanted_scrobbles Thu, 5 Jun 2008 17:38:57 +0000 http://www.last.fm/user/klbostee/journal/2008/06/05/20epfr_most_unwanted_scrobbles Once again, we added some charts on playground. This time they show the tracks and artists that were most frequently deleted by the Last.fm community from their scrobbles. As always, feel free to let us know what you think!]]> http://www.last.fm/user/klbostee/journal/2008/06/05/20epfr_most_unwanted_scrobbles#comments http://www.last.fm/user/klbostee/journal/2008/05/28/1zyy00_top_user-to-user_recommendations Wed, 28 May 2008 13:01:35 +0000 http://www.last.fm/user/klbostee/journal/2008/05/28/1zyy00_top_user-to-user_recommendations We just launched a new playground demo. It's a weekly chart of tracks and artists recommended by users to users. Let us know if you like it!]]> http://www.last.fm/user/klbostee/journal/2008/05/28/1zyy00_top_user-to-user_recommendations#comments http://www.last.fm/user/E1i45/journal/2008/05/20/1zjmr8_islands_of_music Tue, 20 May 2008 14:26:10 +0000 http://www.last.fm/user/E1i45/journal/2008/05/20/1zjmr8_islands_of_music The islands of music playground demonstration is something like a tag cloud where similar tags are located close to each together. The map was created using clustering algorithms.

These algorithms group similar music on islands. Similar islands are placed close to each other. For example, various flavours of metal are located close to each other in the upper right of the map. The map also suggests several more or less continuous transitions. For example, there is a path from folk to doom metal (via psychedelic, progressive rock, and progressive metal).

Another somewhat curious example is the sea of mistagged artist where various flavours of non-English world music can be found. Generally, not all clusters make sense and part of the explanation is that there is plenty of noise in the data.


In more technical terms:

The map is a self-organizing map of 13,000 randomly sampled Last.fm users labelled with tags and artists associated with each user.

Each of these 13,000 users is described with a tag cloud which is extracted from the music the user listens to. This data is normalized in a similar way as described here . One consequence of this is that a large part of alternative indie rock pop is averaged out.

After all the normalization and pre-processing the 13k users are represented by 2000 distinct tags resulting in 13k sparse vectors in a 2k-dimensional tag vector space.

Using singular value decomposition (SVD) the dimensionality is reduced to 120 dimensions. This 120-dimensional space is a latent semantic space in which no distinction is made, for example, between brazil and brasil.

Using k-means clustering 400 prototypical users are computed. Users very close to the zero-vector are not considered for further analysis. (Given the normalization and the latent space mapping, these zero-vector users can be interpreted as either very average users, or so unique that they can’t be described within the 120-dimensional space.)

Using a self-organizing map (SOM) the latent space is mapped to a 2-dimensional visualization space. The SOM has a size of 20 rows and 40 columns. A smoothed data histogram of the SOM is computed and visualized so that clusters show up as islands.]]> http://www.last.fm/user/E1i45/journal/2008/05/20/1zjmr8_islands_of_music#comments