Amazon is well known for their fun feature "Customers who bought this also bought". It is a great way to discover related books.
Internally, that feature is called similarities. Using the feature repeatedly, hopping from detail page to detail page, is called similarity surfing.
A very sharp and experienced developer named Eric wrote the first version of similarities that made it out to the Amazon website. It was great working with Eric. I learned much from him over the years.
The first version of similarities was quite popular. But it had a problem, the Harry Potter problem.
Oh, yes, Harry Potter. Harry Potter is a runaway bestseller. Kids buy it. Adults buy it. Everyone buys it.
So, take a book, any book. If you look at all the customers who bought that book, then look at what other books they bought, rest assured, most of them have bought Harry Potter.
This kind of similarity is not very useful. If I'm looking at the book "The Psychology of Computer Programming", telling me that customers are also interested in Harry Potter is not helpful. Recommending "Peopleware" and "The Mythical Man Month", that is pretty helpful.
Solving this problem is not as easy as it might appear. Some of the more obvious solutions create other problems, some of which are more serious than the original.
After much experimentation, I discovered a new version of similarities that worked quite well. The similarities were non-obvious, helpful, and useful. Heck, while I was at it, I threw in some performance improvements as well. Very fun stuff.
When this new version of similarities hit the website, Jeff Bezos walked into my office and literally bowed before me. On his knees, he chanted, "I am not worthy, I am not worthy."
I didn't know what to say then, and I don't know what to say now. But that memory will stick with me forever.