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All IBM Watson properties can be used in segmentation. If the property is type
List of Objects you must state the relevance score (as a decimal) of the property being selected, the relevance score indicates how relevant the property is to the classified document.
Example: Segmenting users interested in 'auto parts' (as classified by this standard taxonomy) with a maximum score of 0.8
Example: Segmenting users interested in 'Gaming' concepts with a minimum score of 0.8
Example: Segmenting users reading 'joyful' articles with a relevance score more than 0.7 on the topic of 'movies'
Example: Segmenting users reading articles related to 'Spain' with a relevance score of more or equal to 0.8
Example: Segmenting users interested in articles on 'e-cigarettes' with a minimum relevance score of 0.7
Example: Segmenting users reading 'positive' articles with a relevance score more than 0.8
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