From the post:
In the first post in this series, we raised the possibility that graph databases might allow us to analyze event data in new ways, especially where we were interested in understanding the sequences that events occured in. In the second post, we walked through loading Snowplow page view event data into Neo4J in a graph designed to enable pathing analytics. In this post, we’re going to see whether the hypothesis we raised in the first post is right: can we perform the type of pathing analysis on Snowplow data that is so difficult and expensive when it’s in a SQL database, once it’s loaded in a graph?
In this blog post, we’re going to answer a set of questions related to the journeys that users have taken through our own (this) website. We’ll start by answering some some easy questions to get used to working with Cypher. Note that some of these simpler queries could be easily written in SQL; we’re just interested in checking out how Cypher works at this stage. Later on, we’ll move on to answering questions that are not feasible using SQL.
If you dream in markup, ;-), you are probably thinking what I’m thinking. Yes, what about modeling paths in markup documents? What is more, visualizing those paths. Would certainly beat the hell out of some of the examples you find in the XML specifications.
Not to mentioned that they would be paths in your own documents.
Question: I am assuming you would not collapse all the <p> nodes yes? That is for some purposes we display the tree as though every node is unique, identified by its location in the markup tree. For other purposes it might be useful to visualize some paths as collapsed node where size or color is an indicator of the number of nodes collapsed into that path.
That sounds like a Balisage presentation for 2015.