6.7.4 Understanding the Facet Pairs view with correlation values Calculating the correlation value With the Facet Pairs view, you can identify a high correlation of keywords from  the selected facets. Content Analytics requires two sets of search results to  calculate a correlation. Accordingly, you select two facets that represent the two  search result sets of the document set. This section explains how the correlation value is calculated in Figure 6-19 on  page 191 by using the Product facet as the row and Verb facet as the column. To calculate the correlation value, first you must know the following information: Therefore, about 14% of the documents ( 123/852 ) contain the keyword “leak.”  This value is referred as the  density  of the keyword in a given document set. Next, you must look at the intersection cells of the keywords, “orange juice” and  “leak.” You see that the total number of occurrences of documents that includes  both the keywords “orange juice” and “leak” is 67. Thus the density of the  keyword “leak” in the document set for the keyword “orange juice” is 78% (that is  67/86 ).  When you calculate the correlation value, you must consider the ratio of these  two density values as the correlation value: That is, you are interested in the ratio of the following items: In this example, the correlation value of orange juice and leak is calculated as 5.5  (roughly  77%/14% ).  The correlation value calculated in this manner is not reliable especially when the  number of documents, which includes both keywords, is relatively small. For  example, the number of documents that includes keyword B is 2, while the  number of documents that includes keyword C is 100. Then, consider the  number of documents that include keyword A in both document sets. The density  is 50% for both document sets. Which value is more reliable? 192  IBM Watson Content Analytics: Discovering Actionable Insight from Your Content GLYPH<SM590000> The total number of occurrences of “orange juice” is 86. GLYPH<SM590000> The total number of occurrences of “leak” is 123.  GLYPH<SM590000> The entire number of documents in the corpus is 852. GLYPH<SM590000> The density of the given set of documents that includes the specific keyword GLYPH<SM590000> The density of the entire set of the documents in the whole collection GLYPH<SM590000> The density of the keyword “leak” in the document set for the keyword “orange  juice” ( 67/86 = 78% )  GLYPH<SM590000> The density of the keyword “leak” in the entire document set ( 123/852 = 14% )