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图书名称： Data Mining and Knowledge Discovery for Big Data， Studies in Big Data Volume 1
作者：Janusz Kacprzyk, Warsaw, Poland
出版社：Springer International Publishing
页数：314
出版时间：2013
语言：English
格式：pdf
内容简介：
The field of data mining has made significant and far-reaching advances over
the past three decades. Because of its potential power for solving complex
problems, data mining has been successfully applied to diverse areas such as
business, engineering, social media, and biological science. Many of these ap-
plications search for patterns in complex structural information. This trans-
disciplinary aspect of data mining addresses the rapidly expanding areas of
science and engineering which demand new methods for connecting results
across fields. In biomedicine for example, modeling complex biological sys-
tems requires linking knowledge across many levels of science, from genes
to disease. Further, the data characteristics of the problems have also grown
from static to dynamic and spatiotemporal, complete to incomplete, and cen-
tralized to distributed, and grow in their scope and size (this is known as big
data). The effective integration of big data for decision-making also requires
privacy preservation. Because of the board-based applications and often in-
terdisciplinary, their published research results are scattered among journals
and conference proceedings in different fields and not limited to such jour-
nals and conferences in knowledge discovery and data mining (KDD). It is
therefore difficult for researchers to locate results that are outside of their
own field. This motivated us to invite experts to contribute papers that sum-
marize the advances of data mining in their respective fields.Therefore, to
a large degree, the following chapters describe problem solving for specific
applications and developing innovative mining tools for knowledge discovery.
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