Every now and then someone asks 'Why don't you build Collaborative Recommendation into Particls'.

In case you don't know, Collaborative Recommendation is when a system uses the recommendation of many people to 'decide' that a piece of content is worth seeing. So, like Digg for example, if 100 people vote that something is great (vote is a word I use loosely here), then it is probably worth seeing.

There are a few answers to that question.

Particls is really about filtering noise out - not discovering new recommended content (even though we provide some of that functionality just to get novice users started).
There are plenty of other great collaborative recommendation services out there, stick the RSS feed into Particls and there you go.
Google's PageRank and Technorati's Authority is already a form of Collaborative Recommendation - it isn't really very new.
The next generation of Collaborative Recommendation is actually something different. Let's call it Collaborative Filtering 3.0 or... Peer LifeStreams + Personal Relevancy

You have friends (hopefully); they have lifestreams (or at the very least RSS feeds from all their social/sharing sites) - plug their feeds into Particls and we filter out the stuff you don't care about. What's left? Stuff your friends 'recommended' that you actually care about. Collaborative Recommendation done right.

If you want to add me to your Collaborative Recommendation lineup, you can find me on Jaiku