You can view the videos at these links:
Part 1 https://www.youtube.com/watch?v=ui8kjxGmjE0
Part 2 https://www.youtube.com/watch?v=Hma_ho2fHck
The Recommender pattern is made up of one optional knowtifact and two required knowtifacts.
The optional knowledge artifact is a classification tree of the options under consideration. The two required knowtifacts are a context decision tree and a data table that lays out all of the options and their attributes.
In the book I talk about two simple Recommenders: an app that asks a potential knowledge author questions about what they want to achieve and then recommends the best knowledge artifact for the job (the KA Recommender) and a Beach Town Recommender that asks a future traveler a series of questions and then recommends the best beach towns for vacation.
For this example I am going to create a Whiskey Recommender (or "Whisky" Recommender, if you prefer that spelling of the word; I learned in my research that whiskey aficionados feel passionately about this question).
I picked whiskey NOT because I am an expert - I'm not. I picked it because I ran across this great visual in an issue of Fast Company:
This poster, which is very cool looking, appears to be a hopelessly complex constellation of whiskey names and types, but I knew immediately that it was something much more fundamental -- it is a classification tree for whiskeys.
In The Shape of Knowledge, the classification tree is one of my prime examples of the Triangle shape. This whiskey visual doesn't look very much like a triangle, or 'rooted tree', but it is. My first task in building the Whiskey Recommender is to transform this content into a usable form, and I will do that by organizing the basic tree structure shown in the diagram, using KnowtShare.