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Tom Conrad

I've moved my blog to http://tomconrad.net. Visit me there.

Tuesday, April 11, 2006

Pandora at BayCHI Tonight

If you live in the bay area and are interested in learning more about Pandora's approach to user experience and playlist creation stop by tonight's 7:30PM BayCHI meeting:

http://www.baychi.org/program/

Several exciting developments in social search and personalization help users find information: recommendations based on personal tastes, social trends, tags, ratings, popularity, and friends tastes. These methods go beyond the classic search paradigm of relevance and flat lists of results, resulting in different user experience challenges. This panel brings together panelists from Netflix, Live365, Pandora, and digg to explore trends in social search.


Rashmi Sinha has put together a great lineup for the panel including Neil Hunt from Netflix, David Porter from Live365, Kevin Rose from Digg, and Joshua Schachter from del.icio.us. I'm really looking forward to meeting all of these people; I'm a big fan of their work. Hope to see you there.

Please note: this blog has moved to http://tomconrad.net, please do not post comments here.
 

At 3:25 PM, Anonymous raju said...

That's going to be good! I'd love to be there, just happen to be on the other side of the globe. Tell me how it was (maybe in your blog :-).

 
At 9:11 AM, Anonymous jeremy said...

Mmm.. I just read your blog this next morning. Found out about it too late. Ah well, woulda been interesting.

One question and a followup comment:
In the intro to the BayCHI meeting, it talks a bit about developments in social and personalized search. But I don't quite understand the claim:
how do recommendations based on personal tastes, tags, popularity, etc "go beyond the classic search paradigm of relevance"?

Relevance is defined as something that fills my information need, right? Tastes, tags, popularity, etc are just features that help one assess relevance. But they're not somehow "beyond" relevance.

The "classic search paradigm of relevance", as it has been defined since the 1960s (take a look at the Cranfield experiments), is and has always been to find items that meet a user's information need. If that information need is to find something you didn't know existed (e.g. new music) as opposed to simply finding the home page for a company you know does exist, that doesn't matter. In both cases, what you're after is filling your information need, i.e. relevance.

Or is there some other understanding of this that I'm not getting? Wish I coulda made it last night, and asked folks there a bit more about this.

 

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