TechCrunch & Relevant Real-Time Recommendations

Not that I would normally post when someone covers us.  But today on techcrunch some interesting things were said.  Greg Linden of Findory.com did a great job of pointing out the difficulties in dealing with attention data in real-time. I would like to reiterate here what I commented back:

In late 2000, my team started working on an internet marketing technology designed to efficiently collect, organize, analyze, and pull metrics off of hundreds of thousands (to millions) of meta-data transactions per minute. That system was up, fast, scaled nicely, and proved its point by providing marketing lift and supplying outstanding real-time metrics without harassing the user! But… right technology, wrong time…

Today, that system (and its dozen man years of head start) is what we have based our attention streams on. The foundation of our system (client through server) is based on attention streams. We use it on the client to synchronize (and soon client side prioritization) articles among the multiple views (IE, Outlook, more…) we provide. We use it on the server side to synchronize client to server (to mobile). These efficient attention streams are what we will use (with permission and privacy protected) to aggregate users to make relevant recommendations (at the feed and article level), and add community based prioritization of your existing articles, and both timely enough to support today’s requirements.

Comments

[Marshall Kirkpatrick]

Linden is actually from Findory.com, he just blogs via a blogger.com blog. Findory is itself a search company.

[Eric Hayes]

Doh... Yes, I knew that... Thanks Marshall.