数据挖掘(DM)是从数据库中发现知识。
在数据库中发现知识是一个非常活跃的研究领域。
Knowledge discovery in databases is a very active research area.
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。
It is how to find knowledge from DB that results in knowledge Discovery in Database.
如何有效利用这些资源，从数据中发现知识，是当前需要解决的一个问题。
How to use these resources effectively and discover knowledge from data become a problem which should be solved at present.
本文提出一个利用关联规则技术从粗糙集中发现知识的算法，该算法挖掘出的模式具有较高的精确度。
In this paper we propose an algorithm which can mining quantitative association rules in rough set. The pattern mined by this method has high precision.
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。
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。
Rough set, as a theory of data analysis, can deal with uncertainty efficiently , and is one of current hot research directions in knowledge discovery. This paper introduces rough set theory briefly.
本论文还简要讨论了在数据库中发现知识的数据可视化问题，并采用神经网络技术解决该问题，描述了建立一个神经网络数据挖掘的全过程。
Meanwhile, the paper discusses the problem of data visualization, and resolves it using neural network technique, describes the whole process of building a neural network data mining system.
大量的知识、决策制定，和问题解决能力是基于我们在多变事物之中发现行为模式的能力。
Much of our knowledge, decision-making, and problem-solving capacity is based on our ability to spot behavioral patterns among co-varying things.
他们只是想了解网络是如何运行的，并从中发现问题，挑战现有的知识。
They just wanted to know how computer networks worked and saw any barrier between them and that knowledge as a challenge.
你将会在阅读中发现在更多的知识。
And you'll find some more of what there is to say in the readings.
他们只是想了解网络是如何运行的，并从中发现问题，挑战现有的知识。
They just wanted to know how computer networks worked and saw any barrier between them and that knowledge as a challenge. -.
为了从数据集中发现感兴趣的知识规则，须得利用好数据挖掘这一数字信息时代的利器。
In order to find the interested knowledge from datasets, it is required to use data mining which is useful in times of digital information.
从大量的数据资料中发现有价值的信息或知识，达到为决策服务的目的，成为非常艰巨的任务。
In order for decision, it is the hard work that the valuable information or knowledge is discovered from numerous data.
我们已经在我们使用的知识中发现了一个缺口，这个认识的缺口或者缺失或者不足必须得到纠正和弥补。
We have found a gap in the knowledge of the use of the knowledge and this gap or this shortage or lack of understanding must be corrected and put right.
数据挖掘技术可以有效地从大量的客户数据中发现有用的信息和知识，进而可以有效提升客户关系管理的质量，达到提高银行竞争力的目的。
DM can find useful information and knowledge effectively from much customer 's data, and then promote effectively quality of CRM, it reaches the aim which can raise the bank competition.
本文提出了一种基于知识的遥感图像模糊分类算法，在传统的模糊分类方法中加入了从GIS数据库中发现的知识，用它来辅助进行遥感图像分类。
In this paper, a knowledge-based fuzzy image classification method is proposed. In the method, knowledge discovery from GIS is introduced in to assist fuzzy image classification.
为了在这个博客里提供一些基础教育内容，我已经从我最近的研究中搜集并编排了一些笔记，希望你们能从中发现有用的知识。
In an attempt to offer more educational-based content in this blog, I have compiled some notes from my recent researches that I hope you will find informative.
数据挖掘是帮助人们在海量数据中发现信息和知识的工具，广泛应用到各个领域，包括异常检测。
Data Mining Technology, a tool that can discover information and knowledge in large data set, is used many fields, including anomaly detection.
所谓数据挖掘技术就是通过对现实问题进行有效的模式提取，从大量的数据中发现隐藏于其后的规律或数据间的关系，从而分析、提取有用的知识，服务于管理决策。
Data mining picks up the practical issue with effective mode, finds the hiding rule from the abundant data, analyses and gets useful knowledge, serves for the decision-making.
数据挖掘技术可以从大量的数据中发现某些有价值的知识。
Data mining technology can find some valuable knowledge from large amounts of data.
粗糙集理论的特点是不需要提供数据集合以外的任何先验信息，可直接对数据进行分析和推理，从中发现隐含的知识，揭示潜在的规律。
The characteristic of Rough set theory is that it can find out implicit knowledge and reveal latent rules by directly analyzing and reasoning the data without any prior experience of data set.
数据挖掘能从大量的日常积累的数据中发现潜在的、有价值的信息和知识，用于支持决策。
Mining data from a large number of day-to-day accumulation of data found potential, valuable information and knowledge, used to support decision-making.
数据挖掘技术可以从大量数据中发现潜在的、有价值的知识，它给人们在信息时代所积累的海量数据赋予了新的意义。
Data mining techniques can be used to find out potential and useful knowledge from the vast amount of data, and it plays a new significant role to the stored data in the info-times.
数据开采是利用现代统计学知识和计算知识从大型数据库中发现潜在的有用模式的学科。
Data mining can be regarded as a collection of methods for discovery useful pattern from large databases.
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。
This paper discusses our research in discovery useful knowledge from a structured database. This research is an extended on our previous work.
数据挖掘的任务是从海量数据中发现隐含的有用知识，为科学决策提供支持。
The purpose of data mining is to discovery hidden and useful knowledge which can support the science decision from huge amounts of data.
如何从浩如烟海的数据中发现隐藏的有用知识，创造更大的效益是一个迫切需要研究的课题。
How to discover quickly and exactly the useful information and knowledge and how to get more benefits, have become a key research topic.
如何从浩如烟海的数据中发现隐藏的有用知识，创造更大的效益是一个迫切需要研究的课题。
How to discover quickly and exactly the useful information and knowledge and how to get more benefits, have become a key research topic.
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