DKE：数据知识工程
“数据知识工程”在学术和工程领域中常被简称为DKE，这一缩写不仅方便快捷地书写与使用，也利于专业交流。它作为一门交叉学科，融合了数据科学与知识工程的理论与实践，广泛应用于数据处理、知识发现和智能系统构建。通过高效管理海量信息并提炼出有价值的知识，DKE为科研创新和工程应用提供了重要支持。
Data Knowledge Engineering具体释义
Data Knowledge Engineering的英文发音
例句
- Finally, data validation and optimization value finding software is made and integrated into UPOS according to the theory of data mining and knowledge engineering.
- 最后，论文基于数据挖掘的理论和知识工程的增量式开发方法研制了运行优化数据检验软件和优化目标值挖掘软件。
- Meanwhile, classification data mining as an important research content has been widely used in pattern recognition, artificial intelligence and knowledge engineering.
- 分类数据挖掘作为数据挖掘中一个重要的研究内容，已经被广泛应用于模式识别、人工智能和知识工程等领域。
- Through the data mining of these process data, knowledge of parameter optimization and forecast method of output and evaporation intensity were found. Therefore, the engineering operation can be directed.
- 对这些过程数据进行挖掘，可以从中发现参数的优化及产量、蒸发强度的预测方法等知识，从而指导工程实践。
- Based on the summarizing of dam safety monitoring general situation, the external measure data of concrete dam are systematically researched by using the theories and methods of mathematics and mechanics combined with the knowledge of dam engineering.
- 本文在综述大坝安全监测概况的基础上，应用数学、力学的基本理论，结合坝工知识对混凝土坝的外观资料进行了较为全面的分析研究。
- Concept lattice, the main data structure in formal concept analysis theory, has been widely applied to many fields such as machine learning, knowledge discovery, information retrieval and software engineering.
- 概念格作为形式概念分析理论中的核心数据结构，在机器学习、知识发现、信息检索、软件工程等领域得到了广泛的应用。
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