ENTRIES TAGGED "recommendation"
The algorithm's role in discovery and serendipity
It’s NCAA tournament time here in the U.S. and plenty of bracketologists are turning to Nate Silver for his statistical expertise. Silver, of course, is known for his book, The Signal and the Noise, as well as predicting presidential elections and Major League Baseball player performance. I’m not aware of any statistical analysis he’s done in the book recommendation space but I know someone who has applied Silver’s thinking to help us figure out what book we should read next.
I’m talking about Stephanie Sun and a terrific article she wrote called Nate Silverizing Book Recommendations. I encourage you to read the entire piece, even if it’s been awhile since your last statistics class.
The ideal discovery platform requires not one, but many input sources
The ideal content discovery service has yet to be invented. Plenty have tried but none have truly succeeded. The latest is venture is BookScout from Random House. It’s a nifty Facebook app that uses your social graph to help you discover relevant content. As Laura Hazard Owen recently discovered though, it’s far from perfect.
Reading Laura’s post reminded me of something a wise person told me last year: Just because I’m Facebook friends with you doesn’t mean we have the same reading interests. In fact, I’d be willing to bet my reading interests don’t map very well to any of my friends, real or virtual.