It is how to find knowledge from DB that results in knowledge Discovery in Database.
如何从这些海量数据中发现知识，导致了知识发现和数据挖掘领域的出现。
Data Mining, also known as knowledge Discovery in Database, distills knowledge from a mass of data.
数据挖掘就是从海量数据中提取知识，又被称为数据库中的知识发现。
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。
So in facing of challenge of "Much data, but little information", there come Data Mining (DM) and Knowledge Discovery in Database (KDD).
因此，面对“数据丰富，但信息贫乏”的挑战，数据挖掘和知识发现技术应运而生。
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。
Simultaneously, the research development, hot topic and challenges in the filed of data mining and knowledge discovery in database are summarized.
系统地概括了近年来天文学中数据挖掘和知识发现领域研究的进展及其热点，并阐述了其所面临的挑战。
Rough set data analysis in the knowledge discovery in database (KDD) is different to other KDD methods, especially with respect to model assumption.
粗集数据分析不同于其它知识发现方法，特别在模型假设方面的一种方法。
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。
Based on the work stated above, a prototype system that can utilize multi-extending concept lattice classification knowledge discovery in database is implemented.
在上述研究工作的基础上，实现了基于多扩展概念格的分类知识发现原型系统。
Knowledge discovery in database can be define as identifying the effective, original, potential and something that ultimately can be understood as the mode of out of common process.
数据库中知识发现是从数据中识别出有效的、新颖的、潜在有用的乃至最终可理解的模式的非平凡过程。
Rough Sets theory has great superiority in Data Preprocessing because of its particular expression of knowledge, as well as it makes an effective means of knowledge Discovery in Database.
粗糙集理论由于其独特的知识表示方法在数据预处理方面有着得天独厚的优势，同时也成为数据库中知识发现的有效手段。
The data mining is also called the knowledge discovery in database, which discovers from large quantity of data and find authentic, novel and effective model that can be comprehended by people.
数据挖掘可以称为数据库中的知识发现，它是从大量数据中发现并提取隐藏在其中的可信的、新颖的、有效的并能被人理解的模式的高级处理过程。
This paper discusses the essential concepts, the procedure of Mining Association Rules, an active field in KDD (Knowledge Discovery in Database), as well as the open problems faced in this field.
围绕KDD的一个重要发现任务——关联规则发现，介绍了这一领域基本概念、处理技术以及面临的问题。
In view of the characters and designing requirements of platform test system fault diagnosis, a new framework of diagnosis system using knowledge discovery in database (KDD) technology is put forward.
针对平台自动测试系统故障诊断的特点和设计要求，提出了一种将知识发现技术融入故障诊断系统中的新的框架，同时设计了知识发现操作的具体过程。
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。
Data Mining is recently core technologies for an enterprise to analyze large data-sets, and it is a key step in knowledge discovery process and a database technical further expanding.
数据挖掘是近年来企业用以分析大型数据集的核心技术，是知识发现过程中的关键步骤，是数据库技术的进一步扩展。
Data mining is a theory forward in the field of database and decision-making information, It is core of the knowledge discovery.
数据挖掘是数据库和信息决策领域的一个理论前沿，是知识发现的核心部分。
Knowledge discovery process in database is to formalize the knowledge contained in the database into a useful concept.
数据库知识发现的过程就是将数据库中蕴含的知识形式化为有用概念的过程。
Based on theory researches and practical development conditions of fuzzy database, some problems about knowledge discovery are explored in the crime fuzzy database.
根据模糊数据库的理论研究及实际开发状况，对犯罪模糊数据库中知识发现的几个问题进行了探讨。
This paper discusses our research in discovery useful knowledge from a structured database. This research is an extended on our previous work.
讨论了在结构化的数据库中发现有用知识的一些研究工作。
Attributeoriented knowledge discovery method is proved to be a powerful approach for mining incomplete data in the large database in our experiment of this paper.
实验证明利用这种基于属性的知识发现方法处理缺损数据是很有效的。
Attributeoriented knowledge discovery method is proved to be a powerful approach for mining incomplete data in the large database in our experiment of this paper.
实验证明利用这种基于属性的知识发现方法处理缺损数据是很有效的。
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