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Titlebook: Data Mining and Knowledge Discovery for Big Data; Methodologies, Chall Wesley W. Chu Book 2014 Springer-Verlag Berlin Heidelberg 2014 Compu

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發(fā)表于 2025-3-21 16:11:18 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Data Mining and Knowledge Discovery for Big Data
副標(biāo)題Methodologies, Chall
編輯Wesley W. Chu
視頻videohttp://file.papertrans.cn/263/262933/262933.mp4
概述Latest research on data mining.Presents foundations, social networks and applications.Written by leading experts in the field
叢書名稱Studies in Big Data
圖書封面Titlebook: Data Mining and Knowledge Discovery for Big Data; Methodologies, Chall Wesley W. Chu Book 2014 Springer-Verlag Berlin Heidelberg 2014 Compu
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
關(guān)鍵詞Computational Intelligence; Davis Social Links; Foundation on Data Mining and Learning; MoveMining; Opin
版次1
doihttps://doi.org/10.1007/978-3-642-40837-3
isbn_softcover978-3-662-50945-6
isbn_ebook978-3-642-40837-3Series ISSN 2197-6503 Series E-ISSN 2197-6511
issn_series 2197-6503
copyrightSpringer-Verlag Berlin Heidelberg 2014
The information of publication is updating

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Tao Wang,Mandakh Nyamtseren,Jing Pan own needs and perceptions of the situation. They have begun deploying new software platforms to better analyze incoming data from social media, as well as to deploy new technologies to specifically harvest messages from disaster situations.
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Social Media in Disaster Relief, own needs and perceptions of the situation. They have begun deploying new software platforms to better analyze incoming data from social media, as well as to deploy new technologies to specifically harvest messages from disaster situations.
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Paul McCrory,Tsharni Zazryn,Peter Cameronare usually required for action. Aspect extraction and entity extraction are thus two core tasks of aspect-based opinion mining. In this chapter, we provide a broad overview of the tasks and the current state-of-the-art extraction techniques.
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發(fā)表于 2025-3-22 16:33:01 | 只看該作者
Aspect and Entity Extraction for Opinion Mining,are usually required for action. Aspect extraction and entity extraction are thus two core tasks of aspect-based opinion mining. In this chapter, we provide a broad overview of the tasks and the current state-of-the-art extraction techniques.
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發(fā)表于 2025-3-22 20:37:34 | 只看該作者
https://doi.org/10.1007/978-3-642-40837-3Computational Intelligence; Davis Social Links; Foundation on Data Mining and Learning; MoveMining; Opin
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978-3-662-50945-6Springer-Verlag Berlin Heidelberg 2014
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