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 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.

Video Overview of The Shape of Knowledge

I wanted to create a fast and easy entry point to the content of my eBook The Shape of Knowledge. I decided to make a video but I didn't want to do a traditional PowerPoint presentation - too boring - so I created a Prezi for the visual portion of my presentation.

If you're not familiar with Prezi, it is a visual presentation platform that lets you layout your content on a big whiteboard, in any way you want. Then you create a presentation path through the space, zooming in, zooming out, panning back and forth... there are tools that make it easy to create this path, including simple animations within individual frames. It is a real playground for the imagination, and the basic version of the service is free to use.

I like Prezi because I am very visual - that's why I am focused on shape and structure. What I liked about using Prezi as the vehicle to tell my story is that it let me layout my visuals the way I see them in my head, as a tree. But the presentation path is, by definition, a 'line' shape. This made my presentation both a story and an example of the story's main message: that there are best practices in knowledge shaping that make the transmission of knowledge more effective.

Best practice #1: Pick the best shape to store the expert knowledge. My Prezi shape is a composition tree.

Best practice #2: Prune the expert knowledge to fit the context of the current situation. I ended up breaking my story into two parts, the first focusing on the conceptual foundation and best practices, the second focusing on implementation. The unnecessary content was pruned away during the creation of each part.

Best practice #3: Present the solution with the simplest shape possible. The shape of my solution is a line, a linear path that represents my story-line.

I created narration using Adobe Audition and put the videos together using Techsmith's Camtasia. The videos are posted on YouTube.

Here is Part One:

Here is Part Two: