Portable playlists at Media Web Meetup in SF

I’ll be in San Fran on December 11 for the Media Web Meetup at the Songbird offices.

Here’s the event description:

Subject: Portable Playlists and other POSH-ibilities
Speakers: Tantek Çelik, Lucas Gonze, Scott Kveton and Tom Conrad

This Media Web Meetup should be HOT! We are having a panel of people who will lead a discussion on the possibility of portable playlists and other ways for media lovers to carry around their data with themselves as they move around the web.

Think about it…wouldn’t taking that Amazon data with you as you browse other sites (last.fm, iTunes, Pandora, the music web in general) to get better recommendations rock? Perhaps we can get a base discussion of what kinds of solutions there are out there and where to go forward from.

Question: what does POSH (“Plain Old Semantic HTML”, a ) have to do with it? Why must tech religions crush everything in their path? Per Wikipedia:

The purpose of the term ‘POSH’ is to:

  • educate HTML authors who want to use microformats, but haven’t understood the intermediate step of ‘semantic html’ markup.
  • encourage use of the term ‘microformats‘ only for semantic html patterns which have been through the rigor of the microformats process.

6 thoughts on “Portable playlists at Media Web Meetup in SF

  1. APML is the Attention Profile Markup Language. It is a nascent standard for making our taste data portable. You can read more about it at APML.org. I’ve recently built an APML generator for your last.fm data. See tastebroker.org

  2. I could see using this data to power recommendations. How well does non-musical attention data predict musical tastes?

    I guess that non-musical attention data would correlate with age and education, which are real but fairly broad predictors of musical tastes. And some of the attention data would be directly oriented towards the arts, for example if your browsing history contained a lot of visits to hairbands.com.

  3. Pushing this further, the question is portable *recommendations.*

    From http://apml.org/geeks/usecases/ :

    Example
    uses might include…

    Share and remix your APML
    file across various services to create a rich profile of
    your interests. Imagine having access to the interest
    profile Amazon has created for you.
     
    Convert your Lifestream RSS
    feeds to APML to track your Attention across services (using
    something like Engagd).

     
    Upload your APML file to
    Digg to get a customized view of Digg stories that match
    your interests.
     
    Use your APML to filter
    incoming alerts (using something like
    Particls)
     
    Keep control of your own
    Attention Profile – it’s very valuable (read
    Your Rights).
      

    Submit your APML to an
    Attention Brokerage service to allow synchronized access to
    your Attention Profile across all APML compatible services.
    In this way all your sites and services can keep track of
    your changing interests.
     

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