The field values in the input data might be hard to read or might not be intuitively meaningful. For example, input data might contain bar codes. You can map cryptic values to meaningful names by using name mappings. For example, the field values in the input data might be represented by numbers such as 138. The number 138 might represent the article cheese. By creating a name mapping, you can map the field value 138 to the article name Cheese.
When you assign a name mapping to a field value, the meaningful name is written together with the field value into the mining model. When you visualize the model, for example, with Intelligent Miner® Visualization, the meaningful names are displayed instead of the field values.
You can define the same name mappings for different item values. However, because the visualizer displays only the name mappings, the visualizer might show seemingly identical rules for the model although they are not identical because they contain different original item values.