| 书目名称 | Data Mining and Knowledge Discovery for Big Data | | 副标题 | Methodologies, Chall | | 编辑 | Wesley W. Chu | | 视频video | | | 概述 | Latest research on data mining.Presents foundations, social networks and applications.Written by leading experts in the field | | 丛书名称 | Studies in Big Data | | 图书封面 |  | | 描述 | .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 applications search for patterns in complex structural information. In biomedicine for example, modeling complex biological systems 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 centralized 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. .The contributions to this monograph summarize the advances of data mining in the respective fields. This volume consists of nine chapters that address subjects ranging from mining data from opinion, spatiotemporal databases, discriminative subgraph patterns, path knowledge discovery, social media, and privacy issues to the subject of computation reduction | | 出版日期 | Book 2014 | | 关键词 | Computational Intelligence; Davis Social Links; Foundation on Data Mining and Learning; MoveMining; Opin | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-642-40837-3 | | isbn_softcover | 978-3-662-50945-6 | | isbn_ebook | 978-3-642-40837-3Series ISSN 2197-6503 Series E-ISSN 2197-6511 | | issn_series | 2197-6503 | | copyright | Springer-Verlag Berlin Heidelberg 2014 |
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发表于 2025-3-21 16:11:18
