7.3.3 Terms of interest If your collection contains a significant number of problem descriptions, the  terms-of-interest option can help to highlight problem-related terms found, and  list those terms into separate subject and predicate facets. The algorithm does  this by looking at the items surrounding adverbs that typically relate to problems  (“suddenly”, “improperly”) as opposed to  those that typically describe a normal  situation (“properly”). You can use these facets as-is, or pick items from the list  that are interesting to you, and use them to create your own dictionaries or  pattern rules. Figure 7-16 shows a sample Term of Interest view. Terms of interest can be enabled very easily with the administration console, and  there is no additional configuration required. For more details about this feature,  see section 8.1, “Terms of interest” on page 266. Custom dictionaries can be created to flag particular words and their synonyms,  creating facet values for dictionary items found in each document. You can create  a dictionary that is based on candidate words and phrases that are found in other  facets, such as these out-of-box facets: These facets use out-of-box rules, and you might want to refine this output to  remove “noise” to create a facet with a more focused view of the data. For  example, you might want to remove references to any nouns except nouns that  are related to your product or its features. Or, you might want to normalize and  consolidate redundant items, such as recognizing that “New York” and “NY” are  equivalent entries and should be counted in the same facet entry. Figure 7-16 Term of Interest view 7.3.4 Custom dictionaries GLYPH<SM590000> Part of speech  GLYPH<SM590000> Phrase Constituent GLYPH<SM590000> Named Entity GLYPH<SM590000> Terms of interest GLYPH<SM590000> Sentiment  Chapter 7. Performing content analysis  255