在通过数据挖掘发现知识的过程中，不应当停留在原始数据层次上，而应当通过

In the process of discovering knowledge through data mining, we should not stay at the level of original data, but should use concept promotion to express and discover knowledge at a higher level of abstraction. The conceptual level has an important foundation and a wide range of applications in many fields such as data warehousing, data mining, and machine learning.

In the process of discovering knowledge through data mining, we should not stay at the original data level, but express and discover knowledge at a higher abstract level through concept improvement. Conceptual hierarchy plays an important basic role and is widely used in many fields, such as data warehouse, data mining, machine learning and so on<br>

In the process of discovering knowledge through data mining, we should not stay at the original data level, but express and discover knowledge at a higher abstract level through concept promotion. Concept level plays an important fundamental role and is widely used in many fields such as data warehouse, data mining and machine learning.