提出一种将数据挖掘技术与装配工艺知识相融合的白车身装配尺寸偏差源快速诊断方法。
A rapid diagnosis method synthesized data mining technology and assembly process knowledge for body-in-white assembly dimension error sources is presented.
并利用数据挖掘工具，发现隐藏在庞杂信息源中的知识和规律，为目标市场的分析与选择提供有价值的参考信息。
The knowledge and rule discovered by data mining tools are useful information for the analysis and selection of Objective market.
本文首先介绍了股票分析与预测的背景知识和方法，其次对数据挖掘理论做了深入细致的研究，然后着重从以下三个方面展开讨论。
Then do a thorough and meticulous research into the theory of data mining. At last discuss the following three aspects:First of all, focus on the research into financial indexes of stock.
数据挖掘与知识发现技术可以从大量的数据中抽取出隐含的、以往未知而又非常有意义和有用的信息。
Data mining and Knowledge discovery is the technology that can extraction of implicit, previously unknown, and potential useful information from data.
将数据挖掘方法与金融领域知识相结合，研究可疑金融交易识别策略与方法，是我国反洗钱领域的重要基础性工作。
In this paper, we have analyzed the characteristics of Chinese foreign exchange money laundering activities, and combined the decision tree approach with financial domain knowledge.
数据挖掘有着广泛的商业应用潜能，是知识发现与知识管理研究中的一个很有应用价值的新领域。
Data Mining share a wide range of potential commercial applications, knowledge management and knowledge discovery in the study of a promising new areas of application.
粗糙集理论是一种新型的数据挖掘和决策分析方法，利用粗糙集理论进行决策表的知识约简与决策规则挖掘已经成为研究热点。
Rough set theory is a new data mining and decision analysis method. Knowledge reduction and decision rule mining in decision table by using rough set theory has become a research hotspot.
在日常生活中广泛存在着各种时间序列数据，发现时间序列知识、对时间序列进行预测正成为数据挖掘与知识发现的重要内容。
In our daily life, there are various kinds of time series data, and time series prediction becomes one of the important aspects of data Mining and Knowledge Discovery (DMKD).
贝叶斯网络分类器是数据挖掘与知识发现领域研究的主要方法之一。
Bayesian network classifier is one of the main research methods in data mining and KDD domain.
本项目研究XML文档管理的若干关键技术，包括XML文档的存储与查询，XML数据的语义，针对XML数据的知识挖掘等。
This project studied the key technologies for the management of XML documents, including the storage and query of XML documents, the semantics of XML documents, and the knowledge mining, etc.
谁能正确地挖掘与分析隐含于这些数据中的知识，谁就能更好地向用户提供产品与服务。
Who can mine and analyze the knowledge contained in the data correctly will offer product and service to customer better and find more opportunities, thus win the competition.
(一般来讲，数据科学就是从数据中提取信息知识，即是数据挖掘与预测分析的延伸，亦是发掘知识与数据的过程。)所以，通俗来讲，数据科学，就是通过分析数据，来挖掘获得这些数据中的潜在信息。
In general terms, data Science is the extraction of knowledge from data, which is a continuation of the field data mining and predictive analytics, also known as knowledge discovery and data mining.
(一般来讲，数据科学就是从数据中提取信息知识，即是数据挖掘与预测分析的延伸，亦是发掘知识与数据的过程。)所以，通俗来讲，数据科学，就是通过分析数据，来挖掘获得这些数据中的潜在信息。
In general terms, data Science is the extraction of knowledge from data, which is a continuation of the field data mining and predictive analytics, also known as knowledge discovery and data mining.
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