银行仍然会从你的账户中挖掘数据，以便向你出售金融产品，包括一些没有价值的东西，比如信用保险和信用卡保护计划。
Banks will still be mining data from your account in order to sell you financial products, including things of little value, such as credit insurance and credit-card protection plans.
这家公司是越来越多的互联网初创企业之一，他们挖掘非传统形式的数据提供金融服务。
The firm is one of a growing number of internet start-ups that mine unconventional forms of data to offer financial services.
数据挖掘技术在银行领域可应用的范围非常广泛，如客户关系管理、风险分析与控制、资金匹配、金融产品的赢利分析等等。
The application domains of data mining in bank industry are wide, including client relationship management, risk analysis and profit analysis of financial products.
本文具体探讨了金融行业的客户关系管理系统在实施过程的若干关键技术，同时对基于数据挖掘的银行客户关系管理技术进行了研究。
This paper discusses some of the key technologies in the implementation process of CRM systems in financial industry, meanwhile studies the bank CRM technology which basing on data-mining in detail.
基于上述原因，本文将数据挖掘和金融时间序列结合在一起进行研究。
Based on above analysis, this paper integrates the study of data mining and financial time series.
数据挖掘技术在国外的大型商业、金融业、保险业、民航等大型企业得到了广泛应用。
On abroad, data mining technology has extensive application in the large-enterprises, such as business, finance, insurance, civil aviation etc.
KDD技术在金融领域应用，主要集中在客户关系分析与管理方面，对交易数据的挖掘还不多见。
In financial, KDD is mainly used to analysis the custom relationship management. There hasn't many KDD method to be used in transaction data.
金融数据的实时分析，过程控制，规章的遵守，安全应用这些都是基于嵌入式数据库的数据挖掘可以应用的领域。
Analysis of real-time financial data, process control, rule observance, security application are fields in which data mining based embedded mobile database can be used.
数据挖掘技术是一门综合多个学科的从数据中寻找规律的技术，该技术已经成功地应用于金融分析、市场分析、客户关系管理等多个行业。
Data mining is a multi subject comprehensive technology that can discover the rule from data. It has been applied successfully to finance analysis, market analysis, and custom relationship management.
利用数据挖掘技术分析外汇汇率时间序列，从时间序列中获得正确的、隐含的、潜在的信息对于金融领域研究具有重要的现实意义。
Data mining are used to analyze the foreign exchange rate time series and acquire the correct, implicated and hidden information, which has practical significance in the financial field.
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.
摘要：数据挖掘技术目前在商业、金融业等方面都得到了广泛的应用，而在教育领域应用较少。
Absrtact: Currently the data mining technology is extensively applied in commerce, finance, ete, whereas there is little application in education.
摘要：数据挖掘技术目前在商业、金融业等方面都得到了广泛的应用，而在教育领域应用较少。
Absrtact: Currently the data mining technology is extensively applied in commerce, finance, ete, whereas there is little application in education.
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