Data Mining, also referred to as Knowledge Discovery from database, is to abstract the potential, unknown and useful information or pattern from the large database or data warehouse.
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隐含的、事先未知的、潜在有用的信息或模式。
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 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。
Firstly, the paper discusses the process, object and method of knowledge discovery, then introduces the anesthetization case database, the ANN model and the evaluation about the result.
本文首先论述了知识发现的过程、对象及方法，然后介绍了研究中实际使用的麻醉病例数据库、神经网络模型和对结果的检验评价方法。
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。
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。
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。
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。
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。
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。
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。
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 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。
The introduction of approximate theory of rough functional dependency will accelerate the development of knowledge discovery for rough relational database and extend its research field.
该度量的提出及其性质的研究有利于粗糙关系数据库的知识发现及数据查询的研究，并且进一步扩大了粗糙关系数据库的研究领域。
The introduction of approximate theory of rough functional dependency will accelerate the development of knowledge discovery for rough relational database and extend its research field.
该度量的提出及其性质的研究有利于粗糙关系数据库的知识发现及数据查询的研究，并且进一步扩大了粗糙关系数据库的研究领域。
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