本文主要研究适合于大规模科学数据挖掘的分类和聚类的理论和应用。
The main point of this paper is to research the theories and applications of classifying and clustering which is suitable for large-scale science data mining.
现在，犹他大学的计算机科学家设计出了一种新的方法，能简单快速地实施“数据挖掘”或提取与分析巨量数据。
Now, a University of Utah computer scientist has devised a new method for simpler, faster "data mining," or extracting and analyzing massive amounts of such data.
但是当进行完数据分析后，科学家发现，挖掘的信息量比他们此前期待的要丰富得多。
But as they analyzed the data, scientists found everything they were looking for, and more.
最近，我有幸受邀在斯坦福为一门课做了次讲座，课程的名字叫数据挖掘与电子商务，由我的朋友安德烈亚.威根 (Andreas Weigend) 主讲。 他曾任亚马逊首席科学家。
Recently I had the opportunity to guest-lecture a class at Stanford called Data Mining and Electronic Business, which is taught by my friend (and former Chief Scientist at Amazon) Andreas Weigend.
最后通过对赤潮预测的数据挖掘应用分析，验证了系统应用的科学合理性。
At last, the data mining application of the red tide forecast is analyzed, and it proves that the system application is scientific and reas.
数据挖掘是目前信息科学领域最前沿的研究课题之一，在许多领域均有成功的应用范例。
Data mining currently is the research frontier within the information science field. It had success applications in many areas.
本文运用计算机科学领域中的数据挖掘技术，提出了一个城市区域交通流分析预测模型。
In this paper, an analytic and predicting model for urban region traffic flow status is presented by using several data mining technologies.
股票价格行为数据挖掘激发了计算机科学、机器学习及其他领域研究的广泛关注。
Stock price behavior data mining has aroused great concern in research of computer science, economy, machine learning and other fields.
随着全球信息量的爆炸式的增长，数据挖掘技术已成为新世纪计算机科学技术的研究热点。
With an explosive increase in global information, data mining technique has been a focus of the new century computer science and technology research.
在水文领域引入数据挖掘的理论与技术，为解决水文科学研究面临的问题提供了新的思路。
The introduction of data mining theories and technologies to hydrological area provides a new way to settle the problems that the hydrological science confronts with.
聚类分析是数据挖掘中一种重要的挖掘任务和挖掘方法，使得聚类算法的效率和聚类质量在数据挖掘中起着至关重要的作用，也成了计算机科学领域的难题之一。
As an importance task and method for Data Mining, clustering analysis has a great impact on algorithmic efficiency and clustering quality, which is one of difficult problems in Computer Science area.
采用数据挖掘技术来实现对这些信息的科学分析，为企业制定合理的营销方案提供决策支持。
Data Mining can be realized as the good method to analyze these data and provide powerful supporting for making marketing plan and predicating development trend.
函数挖掘是从科学数据中发现有效的函数关系，它是数据挖掘技术的重要研究方向。
Function Mining is an important research direction of data Mining to discover functions hidden in scientific databases.
在短期，可能还有另一种神经科学的研究方法会影响计算，数据挖掘和人工智能。
In the shorter-term, there is another way neuroscience research might influence computation, data mining, and artificial intelligence.
数据挖掘是从庞大的数据集或数据库中提炼有用信息的科学。
Data Mining, which extracts useful information from large data sets or databases, is a rising cross subject.
相较于大多数学者，数据对于计算机科学家甚至更为重要——多年来，他们一直在挖掘他们各种稀奇古怪的数据集。
Even more than most academics, computer scientists need data-and for years, they've mined whatever odd and interesting datasets have come their way.
空间自相关是地理信息科学目前研究的热点问题，作为空间数据挖掘的一种手段，它着重分析了空间实体的聚集程度，阐释了事物之间普遍联系的准则。
As a hot topic in present GIS research, and as one of the ways of spatial data mining, the spatial autocorrelation focuses on spatial data convergence and shows that everything is related with others.
本项研究是受国家自然科学基金资助的，课题名为“基于医学图像数据挖掘技术的研究”。
This research work is a part of the Research of Data Mining on Medical Image supported by the National Natural Science Foundation of China.
数据挖掘的任务是从海量数据中发现隐含的有用知识，为科学决策提供支持。
The purpose of data mining is to discovery hidden and useful knowledge which can support the science decision from huge amounts of data.
前言： 本研究采用文本挖掘技术，从在全球公开的纳米科学和技术研究文献数据库（SCI/ SSCI数据库）中提取技术情报。
Text mining was used to extract technical intelligence from the global open nanotechnology and nano science research literature.
(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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