In this first example, we will have the system create a matrix for us.  I ran a query for CPC:g06f17 and the following are the results.

Note: As applications are granted or removed, patents expire, etc. these results and the matrix will change.

From the Search Results grid, run a matrix by going to Analyze>Concept Landscape Matrix.  The matrix below is the result.

Notice the concepts on the "Level 1" line. The automatic matrix chooses up to two lines deep with terms pulled from your search results. But where do those terms come from?

So you might be asking yourself, where did the system get those rows and headers?  For the assignee column on the left, AcclaimIP finds the top 20 current assignees from the search results we generated, and places them in order.  Pretty simple.  The top columns are a little trickier.  Go back to the search results and click Analyze>Cluster>First 250 Results as shown above.  A new search window will pop up showing the results below.  Notice the results on the left.    

Notice in our new window that the Refine Search panel on the left has changed.  There is now a list of important terms from those first 250 patents (for more on Clustering, see Clustering).  If you look at the list of terms, you will notice that they are in the exact same order as the Level 1 row in our matrix.  When you click to expand one of the term folders from the Refine Search panel's Cluster filters, you will find a second list of terms.  This second subgroup of terms are those that the system has determined are the the most relevant terms that can be linked with the level one term.  These are the Level 2 row terms in our matrix.