Themes are the main ideas in a document. Themes can be concrete concepts such as Oracle Corporation, jazz music, football, England, or Nelson Mandela; themes can be abstract concepts such as success, happiness, motivation, or unification.
Themes can also be groupings commonly defined in the world, such as chemistry, botany, or fruit. Themes are the noun phrases or words in the text with
contextual relevance scores. Theme extraction tells you the important words or phrases being used in the text. Themes once extracted are then scored for contextual relevance.
Themes differ from the classifiers in the sense that themes tell you exact phrases or words being used while as classifiers identify the broad topics. Themes are useful for discovery purposes. Themes will allow you to actually see that there is a new aspect to the conversation that may be important to consider, which your classifiers won’t be able to catch.
Themes do a very good job in uncovering the actual context in the text. With the addition of contextual scoring information themes are even more useful in finding out important context from the text and also comparing across similar pieces of text
over a period of time.
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