在这些目录中，概念并非只是元数据的属性，或者是标目的一种形式，它是包含很多信息的参照点，人们可以借由它发现知识资源。
In these catalogs, the concepts aren't simply metadata attributes, or headings in a list of choices, but information-rich reference points for finding knowledge resources.
半结构化数据是网络中一种重要的数据形式，其数据抽取和知识发现研究是半结构化数据各项研究的核心。
Semi-instructured data is a kind of the important type in networks, and its data extracting and knowledge discovery is the core for semi-structured researches.
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。
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.
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。
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.
数据挖掘技术是对大量数据进行分析，发现数据中隐藏知识的一种技术。
Date mining is a technology that it can find hidden knowledge in a large amount of data.
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.
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.
发现了的知识可以被用于信息管理、查询优化、决策支持、过程控制等，还可以用于数据自身的维护。
Discovered knowledge can be used for information management, information optimization, decision support, process control, but also can be used for the maintenance of their own 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。
Data Mining, also known as knowledge Discovery in Database, distills knowledge from a mass of data.
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.
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。
The process of knowledge discovery in time series includes preprocessing of time series data, attributes reduction and rules extraction.
许多早期KM系统的设计，要求人们向数据库中输入材料或者创建个人档案，来帮助大家发现专门的知识和技术，从而实现组织中信息的获取。
Many early KM systems were designed to capture corporate information by requiring people to enter stuff into databases or to create personal profiles to help people find expertise.
因此，适用于具有概率统计特征的数据采掘和知识发现问题，尤其是样本难以获取或代价过于昂贵的问题。
Therefore, it is the same with Data Mining with probability statistic character and knowledge discovery problems, especially with die problems that obtain sample information or need high cost.
因此，适用于具有概率统计特征的数据采掘和知识发现问题，尤其是样本难以获取或代价过于昂贵的问题。
Therefore , it is the same with data mining with probability statistic character and knowledge discovery problems , especially with die problems that obtain sample information or need high cost.
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.
提出了基于数据抽取器的知识发现模型。
In this paper, a knowledge discovery model based on data extractor is proposed.
时间序列相似性模式搜索是营销时间序列数据仓库中知识发现领域的一个研究热点。
The similarity pattern query about time series is one of the research hotspots in knowledge discovering in the time series database.
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.
离群数据的发现，往往可以使人们发现一些真实的、但又出乎意料的知识。
Outlier data mining can help people discover the true and unexpected information.
数据采掘，也称数据库中的知识发现。
Data mining, also known as knowledge discovery in databases.
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.
然而，众所周知，数据库中往往存在冗余数据、缺失数据、不确定数据和不一致数据等诸多情况，这些数据成了发现知识的一大障碍。
However, as well known, there are many issues in databases, such as redundant data, missing data, uncertain data, inconsistent data, and so on, they are the barriers to knowledge discovery.
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 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.
而概念格正是从数据中进行概念发现的有力工具，用来发现数据中隐藏的知识模式。
Concept lattice is a powerful tool for concept discovery from data, used to extract hidden knowledge pattern in data.
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。
Active Spatial data mining technology is used in the processes of alarm data fusion, data mining and knowledge discovery.
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.
数据挖掘工具将为基于数据仓库的决策支持系统开发提供良好的技术支持，以发现数据仓库中潜在的知识。
Data mining provides good technology support for data warehouse-based decision support system, and data mining tools can directly mining in data warehouse for discovering potential knowledge.
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, 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, referred to as knowledge discovery in databases, is the extraction of patterns representing valuable knowledge implicitly stored in large databases or data warehouses.
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