Data Mining and Knowledge Discovery

PUBLISHED


Viewing: 1 - 10 of 110
Published:
March 12, 2014
Author(s):
Stephan Kudyba
There is an ongoing data explosion transpiring that will make previous creations, collections, and storage of data look trivial. Big Data, Mining, and Analytics: Components of Strategic Decision Making ties together big data, data mining, and analytics to explain how readers can leverage them to 
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Published:
January 28, 2014
Editor(s):
Marie-Francine Moens, Juanzi Li, Tat-Seng Chua
Originating from Facebook, LinkedIn, Twitter, Instagram, YouTube, and many other networking sites, the social media shared by users and the associated metadata are collectively known as user generated content (UGC). To analyze UGC and glean insight about user behavior, robust techniques are needed 
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Published:
December 19, 2013
Editor(s):
Jay Liebowitz
Together, Big Data, high-performance computing, and complex environments create unprecedented opportunities for organizations to generate game-changing insights that are based on hard data. Business Analytics: An Introduction explains how to use business analytics to sort through an ever-increasing 
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Published:
December 14, 2013
Author(s):
Subrata Das
Learn How to Properly Use the Latest Analytics Approaches in Your Organization Computational Business Analytics presents tools and techniques for descriptive, predictive, and prescriptive analytics applicable across multiple domains. Through many examples and challenging case studies from a variety 
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Published:
December 11, 2013
Author(s):
Haiping Lu, Konstantinos N. Plataniotis, Anastasios Venetsanopoulos
Due to advances in sensor, storage, and networking technologies, data is being generated on a daily basis at an ever-increasing pace in a wide range of applications, including cloud computing, mobile Internet, and medical imaging. This large multidimensional data requires more efficient 
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Published:
December 05, 2013
Editor(s):
Rajendra Akerkar
Due to market forces and technological evolution, Big Data computing is developing at an increasing rate. A wide variety of novel approaches and tools have emerged to tackle the challenges of Big Data, creating both more opportunities and more challenges for students and professionals in the field 
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Published:
November 14, 2013
Author(s):
Epaminondas Kapetanios, Doina Tatar, Christian Sacarea
This book introduces the semantic aspects of natural language processing and its applications. Topics covered include: measuring word meaning similarity, multi-lingual querying, and parametric theory, named entity recognition, semantics, query language, and the nature of language. The book also 
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$129.95
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Published:
November 04, 2013
Author(s):
Liang Sun, Shuiwang Ji, Jieping Ye
Similar to other data mining and machine learning tasks, multi-label learning suffers from dimensionality. An effective way to mitigate this problem is through dimensionality reduction, which extracts a small number of features by removing irrelevant, redundant, and noisy information. The data 
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Published:
October 25, 2013
Editor(s):
Markus Hofmann, Ralf Klinkenberg
Powerful, Flexible Tools for a Data-Driven WorldAs the data deluge continues in today’s world, the need to master data mining, predictive analytics, and business analytics has never been greater. These techniques and tools provide unprecedented insights into data, enabling better decision making 
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Published:
September 11, 2013
Author(s):
Vlad Atanasiu
Expert Bytes: Computer Expertise in Forensic Documents — Players, Needs, Resources and Pitfalls —introduces computer scientists and forensic document examiners to the computer expertise of forensic documents and assists them with the design of research projects in this interdisciplinary field. 
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Data Mining "Nobel Prize" Awarded to Series Editor Vipin Kumar

The ACM SIGKDD 2012 Innovation Award, the highest award for technical excellence in the field of Knowledge Discovery and Data Mining (KDD), has been awarded to Prof. Vipin Kumar for his technical contributions to foundational research in data mining and its applications to mining scientific and climate data. Prof. Kumar is the editor of the Chapman & Hall/CRC Data Mining and Knowledge Discovery Series. He has pioneered research in the areas of high performance and parallel data mining. His research group has also been at the forefront in the development of data-driven discovery methods for analyzing global climate and ecosystem data.

 

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