作为一个结果，在地铁施工安全风险可以自动从数据库知识发现。
As a result, safety risks in metro construction can be automatically identified from the knowledge database.
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。
Knowledge discovery process in database is to formalize the knowledge contained in the database into a useful concept.
数据挖掘，或者叫做数据库知识发现，是一种自动在大量数据中寻找具有某种相同属性集合的技术。
Data mining, also known as knowledge-discovery in databases (KDD), is the practice of automatically searching large stores of data for patterns.
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。
Some methods for dividing continuous attributes in KDD (knowledge discovery in database) and a method based on VDM (value difference metric) are presented.
介绍了数据库知识发现(KDD)活动的展开要求，着重从它的技术处理流程来分析它的特性及其存在价值与意义。
This article introduces the KDD activity the request that launch, and puts great emphasis on its characteristic and value by technique processing.
可利用数据分级整合、多智能体通信以及数据库知识发现等手段相结合实现从广域监控系统(WAMS)海量数据中提取有用的信息。
By combining data gradation, multi-agent communication and knowledge discovery in data-base, the useful information can be extracted from WAMS (Wide-Area Monitoring System).
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(DM)是从数据库中发现知识。
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.
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。
Writer proposes a framework for the automated translation of the output from knowledge discovery systems to active database rules.
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.
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。
The knowledge discovery and data mining tool display their strong points in handling the great capacity database.
数据采掘，也称数据库中的知识发现。
Data mining, also known as knowledge discovery in databases.
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。
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.
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。
Data mining is a theory forward in the field of database and decision-making information, It is core of the knowledge discovery.
数据库中的知识发现是指在大型数据集中识别有效、新奇、潜在有用、且最终可理解模式的非平凡的过程。
Knowledge discovery in databases is the nontrivial process of identifying valid, novel, potentially useful, and ultimately understandable patterns in large data set.
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.
空间数据挖掘技术为环境数据库的知识发现提供了有效的途径。
Spatial data mining technology offers valuable means for discovering knowledge in environmental database.
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.
数据挖掘主要是用来找出隐藏在数据库当中那些有用的而未被发现的知识。
Data mining is the discovery of useful and potential knowledge hiding in databases.
数据采掘是数据库中知识发现的核心，详细描述了数据采掘中概念树方法在模糊性问题中的应用。
Data mining is the core of knowledge discovery in databases. Concept tree method is one of the most important methods. In this paper, presentation of an approach to deal with fuzziness was discussed.
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。
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.
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.
数据挖掘通常是高度结构化的信息应用到大型数据库，以发现新的知识。
Data mining is typically applied to large databases of highly structured information in order to discover new knowledge.
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.
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.
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.
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.
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