iORDER: Mining Implicit Domain Orders.

ICDE(2023)

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摘要
In this demonstration paper, we describe iORDER, a tool that identifies implicit domain orders in data, such as Small Medium Large. iORDER extends the machinery of order dependency discovery to identify and rank interesting orders. Using real-world data, we showcase how implicit orders help users interpret the semantics of ordered data, how to interactively validate implicit orders to aid in the discovery process, and how to apply implicit orders to applications including data profiling, data mining and knowledge bases.
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关键词
data mining,data profiling,implicit domain orders mining,iORDER,knowledge bases,order dependency discovery,ordered data
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