Data mining, referred to as knowledge discovery in databases, is the extraction of patterns representing valuable knowledge implicitly stored in large databases or data warehouses.
数据挖掘，又称数据库中的知识发现，是指从大型数据库或数据仓库中提取具有潜在应用价值的知识或模式。
Knowledge discovery in databases is the nontrivial process of identifying valid, novel, potentially useful, and ultimately understandable patterns in large data set.
数据库中的知识发现是指在大型数据集中识别有效、新奇、潜在有用、且最终可理解模式的非平凡的过程。
Applying KDD (Knowledge Discovery in Databases) technology in data analysis is helpful to improve data-analysis ability and productivity in photosensitive materials enterprises.
应用KDD技术进行数据分析，对于提高感光材料企业数据分析水平和生产效率具有积极意义。
Data mining, also known as knowledge-discovery in databases (KDD), is the practice of automatically searching large stores of data for patterns.
数据挖掘，或者叫做数据库知识发现，是一种自动在大量数据中寻找具有某种相同属性集合的技术。
Data mining, also known as knowledge-discovery in databases (KDD), is the practice of automatically searching large stores of data for patterns.
数据挖掘，或者叫做数据库知识发现，是一种自动在大量数据中寻找具有某种相同属性集合的技术。
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