Friday, June 27, 2014

Creating a Recommender

I am going to do a series of posts that document the process of creating an app using a knowledge pattern. I am going to use a particular pattern we call a 'Recommender'. The Recommender pattern is shown in both The Shape of Knowledge eBook and in Part 2 of the video series that provides an overview of the eBook's content.

You can view the videos at these links:
Part 1
Part 2

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.

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