"Imperfect and internal rhymes are two important features in rap music previously ignored in the music information retrieval literature. We developed a method of scoring potential rhymes using a probabilistic model based on phoneme frequencies in rap lyrics. We used this scoring scheme to automatically identify internal and line-final rhymes in song lyrics and demonstrated the performance of this method compared to rules-based models. We then calculated higher-level rhyme features and used them to compare rhyming styles in song lyrics from different genres, and for different rap artists. We found that these detected features corresponded to real- world descriptions of rhyming style and were strongly characteristic of different rappers, resulting in potential applications to style-based comparison, music recommendation, and authorship identification." Awesome, and something I am going to sit down and read properly.

"Both within the academy and within tech startups, we’ve been hearing some similar questions lately: Where can I find a good data scientist? What do I need to learn to become a data scientist? Or more succinctly: What is data science?" Great starting point; looking forward to more from the blog.

"...don’t confuse this kind of data exploration, where the goal is to size up the data, with building proper data plumbing, where you want robustness and maintainability. Perl and bash scripts are nice for the former, but can be a nightmare for building data pipelines." Lots of good stuff in this article; this was a highlight.

Excellent, detailed article on how Microsoft calculate TrueSkill - an algorithm for matching you to players about in your skill level. This is what is used every time you hit "game with strangers" on an XBL title, basically. Fascinating, detailed, not too challenging if you take it slow/steady - and the implementation is on github...

"Being NOTES and SLIDES on a talk given at PLAYFUL 09, concerning CHARLES BABBAGE, HEATH ROBINSON, MENACE and MAGE" Awesome; shame I couldn't be there. I wondered where that link about Michie had come from a few weeks ago...

"Someone at work recently asked how he should go about studying machine learning on his own. So I’m putting together a little guide." Ooh, useful. Lots of starting points for machine learning in R.

"This page will maintain list of AI related libraries for the Ruby programming language." Some interesting stuff here, although it's all in varying degrees of maturity...