数据挖掘(DM)是从数据库中发现知识。
本系统采用数据挖掘技术从已有的产品数据库、知识库和规则库中获取有用信息和知识以支持产品概念设计。
This system adopts data mining technique to obtain useful information and knowledge from existing products database, knowledge storehouse and regulation storehouse to support conceptual design.
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.
采用数据挖掘技术从已有的产品的数据库、知识库、规则库中获取有用的信息和知识来有效地支持机械产品概念设计。
This system adopts data mining technique and obtains useful information and knowledge from existing products database, knowledge storehouse and regulation storehouse to support conceptual design.
21世纪是知识经济的时代，面对数据爆炸而知识贫乏的现实，人们提出数据挖掘思想，并将其广泛应用到数据库管理的各个领域。
In the 21st century of the knowledge and economic time and facing with the fact of bursting data but poor knowledge, data mining has been put forward and applied in many fields of database management.
数据挖掘是从大型数据库的数据中提取人们感兴趣的知识，这些知识是隐含的、事先未知的潜在有用信息。
Data Mining is a domain which tries to extract knowledge and interesting information from very large-scale databases. This knowledge is hidden, unknown, but potentially useful.
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.
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.
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.
从海量的数据中提取知识和信息是数据挖掘解决的主要问题、对处理数据库的规模不断扩大，而导致信息杂乱的主要方法。
The data extracted from the mass of knowledge and information are the major problems in data mining, processing database of scale unceasingly expands, the main methods to information messy.
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.
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 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，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.
结果：挖掘结构化报告归档数据库中诊断报告的数据资料，形成带有12个节点的疾病知识库决策树，在知识库中存储。
RESULTS: To mine date in archiving database of SR and form the decision tree in disease knowledge base with 12 nodal points, which stored in knowledge base.
从医嘱数据库的药物医嘱序列中挖掘出的知识既可用于评价治疗质量，又可为准确、快速地制定安全有效的药物治疗方案提供必要的依据。
Knowledge mined from sequence of doctors advice for medicine can not only evaluate treatment quality but also provide necessary basis for establishing a safety and effective medicine treatment plan.
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.
空间关联规则挖掘是在空间数据库中进行知识发现的一类重要问题。
Spatial association rule discovery in spatial databases is a very important data mining task.
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.
数据挖掘是从数据库的大量数据中提取隐含的、未知的并有潜在价值的信息和知识的过程。
Data mining is the process that extracts hidden, unknown and the potential value of information and knowledge form large amounts of data of the database.
数据挖掘是一项较新的数据库技术，它基于大量数据所构成的数据库，从中发现潜在的、有价值的信息——称为知识，用于支持决策。
Data Mining is a newer database technique which aims at discovering potential and valuable pattern that is called as knowledge. The knowledge discovered can be used for decision-making.
铜矿专家系统中知识库和规则库的保存和管理使用了数据库开发技术，采用数据挖掘作为知识发现的新手段。
The database development skills were applied to store and manage the knowledge and the rules while the knowledge founding adopted data mining technology.
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.
数据挖掘是从大型数据库的数据中提取人们感兴趣的知识，这些知识是隐含的、事先未知的潜在有用的信息。
Data Mining is a domain that tries to extract knowledge and interesting information from very large-scale databases. This knowledge is hidden, unknown, but potentially useful.
MDMP用于从多媒体数据库中挖掘出隐含的用户感兴趣的知识。
The MDMP can mine implied knowledge on user interest in MDB.
数据挖掘是近年来数据库领域中出现的一个新兴研究热点，它是从大量数据中获取知识。
Data mining (DM) is a new hot research point in database area. Data mining gets knowledge from large quantity of data.
数据挖掘是近年来数据库领域中出现的一个新兴研究热点，它是从大量数据中获取知识。
Data mining (DM) is a new hot research point in database area. Data mining gets knowledge from large quantity of data.
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