Thanks for your comments guys. Both of you make very interesting
points.

Thomas, I never considered this point of view; that the system would
always be one step behind the users current interests.

However, in reality, do users interests change rapidly? I would guess
a regular use exhibits the same habits over time, with subtle changes
in interest.

I like what you said, John, in your blog post, 
 
"we need to ensure such personalisation enables us to exclude what
we know you will not like, keeping the edges of what you might like
very fuzzy indeed"

I love Last.fm too. I like the similar artist feature although, I
don't use it as often as I should. I also use Amazon recommendations
regularly.

I don't think it's fair to say these systems inhibit serendipity.
Users can still stumble across new things even if it's through a
system that learns what they like.

I think both your points raise important questions about the
algorithm and weighting in the system, rather than the principle.

To aid serendipity and discovery, the system could track trends
across the site, so we can see what the "crowd" is interested in.
These trends, our understanding of the individual user along with
editorial control could offer a more rounded experience of content.

Non?



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Posted from the new ixda.org
http://www.ixda.org/discuss?post=46208


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