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## 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. 

## 7.3.4 Custom dictionaries 

<img src='content_image/996433.jpg'>

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: 

GLYPH<SM590000> Part of speech 

GLYPH<SM590000> Phrase Constituent 

GLYPH<SM590000> Named Entity 

GLYPH<SM590000> Terms of interest 

GLYPH<SM590000> Sentiment 

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. 

