anchor.diff:  
   Log records and other data indexed in Solr have connections between them that can be seen as a distributed graph.
   Graph expressions provide a mechanism for identifying root nodes in the graph and walking their connections.
  -The general goal of the graph walk is to materialize a specific subgraph and perform link analysis to understand
  +The general goal of the graph walk is to materialize a specific *subgraph* and perform *link analysis* to understand
   the connections between nodes.
   
   In the next few sections below we'll review the graph theory behind Solr's graph expressions.
  
positive.code: === Node Scoring and Temporal Anomaly Detection
  
  The concept of node scoring can be applied to temporal graph queries to find events that are
  both correlated with a set of root events and *anomalous* to the root events.
  The degree calculation establishes the correlation between events
  but it does not establish if the event is a very common occurrence in
  the entire graph or specific to the subgraph.
  
negative.code: 
  The `random` function is searching the baskets collection with the query `product_s:butter`, and
  returning 3 random samples. Each sample contains the `basket_s` field which is the basket id.
  The three basket id's that are returned by the random sample are the *root nodes* of the graph query.
  
  The `nodes` function is the graph query. The nodes function is operating over the three root nodes returned
  by the random function.
  