How to analyze these data to find valuable knowledge and principle has become a hot spot in knowledge discovery.
如何有效地分析利用这些数据，从中发现有价值的知识和规律已成为知识发现领域跨学科研究的热点。
Rough set, as a theory of data analysis, can deal with uncertainty efficiently , and is one of current hot research directions in knowledge discovery.
粗集作为一种数据分析理论，能有效地从不确定性的数据中发现知识，是目前在知识发现领域研究的热点之一。
This paper presents a new idea of knowledge element indexing, which is considered a foundation of knowledge integration and knowledge discovery across domain.
本文提出了知识元标引的新概念，认为知识元标引是实现跨领域知识集成与知识发现的基础。
Digital is not only an effective way to achieve conservation and utilization of TCM ancient books, but also the foundation of deep development and knowledge discovery.
数字化是实现中医古籍保护和利用的有效途径，也是中医古籍深度开发和知识发现的基础。
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。
Data Mining (DM) is the knowledge discovery from databases.
数据挖掘(DM)是从数据库中发现知识。
Data mining, also known as knowledge discovery in databases.
数据采掘，也称数据库中的知识发现。
In this paper, a knowledge discovery model based on data extractor is proposed.
提出了基于数据抽取器的知识发现模型。
So, knowledge discovery and data mining are proposed with a new study field developed.
因此，知识发现和数据挖掘应运而生，成为一个新的研究领域。
So a reduction algorithm of attribute for personalized knowledge discovery was designed.
为此，设计了一种面向个性化知识发现的属性约简算法。
The process of attribute reduction is analyzed in assembly knowledge discovery based on rough set.
分析了基于粗糙集理论的装配知识发现中属性归约的过程。
This paper discussed the problem of enterprise marketing knowledge discovery based on network computing.
本文探讨了基于网络计算的企业市场营销知识获取的几个问题。
This paper mainly focuses on knowledge discovery based on concept lattice, and extended concept lattice model.
本文主要对基于概念格模型的知识发现进行研究，并对经典概念格模型进行了扩展。
The knowledge discovery and data mining tool display their strong points in handling the great capacity database.
知识发现及数据挖掘工具在处理海量数据库时显示了它们的长处。
A problem in the information system and knowledge discovery, is a problem of processing optimal knowledge reduction.
最佳知识约简问题是信息系统与知识发现中面临的一个重要问题。
This paper introduces neural networks technology based on data mining and knowledge discovery for inventory problems.
该文介绍了使用基于数据挖掘和知识发现的神经网络技术来解决库存问题的方法。
Active Spatial data mining technology is used in the processes of alarm data fusion, data mining and knowledge discovery.
其中主动空间数据挖掘技术主要体现在数据融合，数据挖掘和知识发现的过程中。
Fuzzy cluster is one of the branches of knowledge discovery in database (KDD). And neural network is a good tool for clustering.
模糊聚类是目前知识发现(KDD)领域中的研究分支之一，而神经网络是用于聚类的良好工具。
Writer proposes a framework for the automated translation of the output from knowledge discovery systems to active database rules.
作者对知识发现系统的输出提出了一种自动转换到主动数据库规则的结构。
It is a process of spatial knowledge discovery and data mining. It sums up a modeling problem of the GIS-based reservoir evaluation.
其本身就是一个空间知识发现和挖掘的过程，实质可归结为基于GIS的油气储层评价建模问题。
Altogether, these examples illustrate how literature analysis can be employed to support knowledge discovery in biomedical research.
总之，这些例子阐明了文献分析如何能够被利用以支持生物医学研究中的知识发现。
The process of knowledge discovery in time series includes preprocessing of time series data, attributes reduction and rules extraction.
知识发现的过程包括时间序列数据预处理、属性约简和规则抽取三部分。
Most data mining tools for knowledge discovery generally use rule discovery and decision tree technology to extract data patterns and rules.
用于知识发现的大部分数据挖掘工具均采用规则发现和决策树分类技术来发现数据模式和规则。
Both online analytical processing (OLAP) and knowledge discovery in database (KDD) are advanced modes of information resources exploitation.
数据的在线分析与知识发现是开发信息资源的高级形式。
Main measure indexes of information effectiveness in historical archives are the difficulty of knowledge discovery, demand, accessibility and effects.
历史档案情报效用的主要衡量指标是知识发现难易度、需求量、可获取性和使用效果。
The knowledge discovery of information system essentially is the problem that how to classify the objects according to the characteristic of attributes.
信息系统的知识发现问题本质上是按照属性特征将对象进行分类的问题。
A knowledge discovery method based on analysis results is put forward for discovering underlying design rules and knowledge embedded in analysis results.
为了发现隐含在模拟结果中潜在的规律和知识，提出了一种基于板料成形数值模拟的知识发现方法。
In this paper, the generation of maximally generalized rules in the course of classification knowledge discovery based on rough sets theory is discussed.
讨论了基于粗糙集理论的分类知识发现中最大泛化规则的生成。
Some methods for dividing continuous attributes in KDD (knowledge discovery in database) and a method based on VDM (value difference metric) are presented.
介绍了在数据库知识发现(KDD)中将连续属性离散化的一些方法，并提出使用值差分度量离散化的算法。
The paper focuses on the properties of complex uncertainty system, and associates knowledge discovery theory and methods with prediction theory and methods.
针对复杂不确定性系统特性，将知识发现理论方法与预测理论方法有机结合起来。
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