Advances In Knowledge Discovery And Data Mining Part I
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Advances In Knowledge Discovery And Data Mining
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Author : Joshua Zhexue Huang
language : en
Publisher: Springer
Release Date : 2011-05-27
Advances In Knowledge Discovery And Data Mining written by Joshua Zhexue Huang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-05-27 with Computers categories.
The two-volume set LNAI 6634 and 6635 constitutes the refereed proceedings of the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2011, held in Shenzhen, China in May 2011. The total of 32 revised full papers and 58 revised short papers were carefully reviewed and selected from 331 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas including data mining, machine learning, artificial intelligence and pattern recognition, data warehousing and databases, statistics, knowledge engineering, behavior sciences, visualization, and emerging areas such as social network analysis.
Advances In Knowledge Discovery And Data Mining
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Author : Jinho Kim
language : en
Publisher: Springer
Release Date : 2017-04-25
Advances In Knowledge Discovery And Data Mining written by Jinho Kim and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-25 with Computers categories.
This two-volume set, LNAI 10234 and 10235, constitutes the thoroughly refereed proceedings of the 21st Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2017, held in Jeju, South Korea, in May 2017. The 129 full papers were carefully reviewed and selected from 458 submissions. They are organized in topical sections named: classification and deep learning; social network and graph mining; privacy-preserving mining and security/risk applications; spatio-temporal and sequential data mining; clustering and anomaly detection; recommender system; feature selection; text and opinion mining; clustering and matrix factorization; dynamic, stream data mining; novel models and algorithms; behavioral data mining; graph clustering and community detection; dimensionality reduction.
Feature Selection For Knowledge Discovery And Data Mining
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Author : Huan Liu
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Feature Selection For Knowledge Discovery And Data Mining written by Huan Liu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
As computer power grows and data collection technologies advance, a plethora of data is generated in almost every field where computers are used. The com puter generated data should be analyzed by computers; without the aid of computing technologies, it is certain that huge amounts of data collected will not ever be examined, let alone be used to our advantages. Even with today's advanced computer technologies (e. g. , machine learning and data mining sys tems), discovering knowledge from data can still be fiendishly hard due to the characteristics of the computer generated data. Taking its simplest form, raw data are represented in feature-values. The size of a dataset can be measUJ·ed in two dimensions, number of features (N) and number of instances (P). Both Nand P can be enormously large. This enormity may cause serious problems to many data mining systems. Feature selection is one of the long existing methods that deal with these problems. Its objective is to select a minimal subset of features according to some reasonable criteria so that the original task can be achieved equally well, if not better. By choosing a minimal subset offeatures, irrelevant and redundant features are removed according to the criterion. When N is reduced, the data space shrinks and in a sense, the data set is now a better representative of the whole data population. If necessary, the reduction of N can also give rise to the reduction of P by eliminating duplicates.
Data Mining And Knowledge Discovery For Process Monitoring And Control
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Author : Xue Z. Wang
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Data Mining And Knowledge Discovery For Process Monitoring And Control written by Xue Z. Wang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
Modern computer-based control systems are able to collect a large amount of information, display it to operators and store it in databases but the interpretation of the data and the subsequent decision making relies mainly on operators with little computer support. This book introduces developments in automatic analysis and interpretation of process-operational data both in real-time and over the operational history, and describes new concepts and methodologies for developing intelligent, state space-based systems for process monitoring, control and diagnosis. The book brings together new methods and algorithms from process monitoring and control, data mining and knowledge discovery, artificial intelligence, pattern recognition, and causal relationship discovery, as well as signal processing. It also provides a framework for integrating plant operators and supervisors into the design of process monitoring and control systems.
Advances In Knowledge Discovery And Data Mining Part I
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Author : Pang-Ning Tan
language : en
Publisher: Springer
Release Date : 2012-05-10
Advances In Knowledge Discovery And Data Mining Part I written by Pang-Ning Tan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-10 with Computers categories.
The two-volume set LNAI 7301 and 7302 constitutes the refereed proceedings of the 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2012, held in Kuala Lumpur, Malaysia, in May 2012. The total of 20 revised full papers and 66 revised short papers were carefully reviewed and selected from 241 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas. The papers are organized in topical sections on supervised learning: active, ensemble, rare-class and online; unsupervised learning: clustering, probabilistic modeling in the first volume and on pattern mining: networks, graphs, time-series and outlier detection, and data manipulation: pre-processing and dimension reduction in the second volume.
Advances In Machine Learning And Data Mining For Astronomy
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Author : Michael J. Way
language : en
Publisher: CRC Press
Release Date : 2012-03-29
Advances In Machine Learning And Data Mining For Astronomy written by Michael J. Way and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-03-29 with Computers categories.
Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining techniques in astronomy. Due to the massive amount and complexity of data in most scientific disciplines, the material discussed in this text transcends traditional boundaries between various areas in the sciences and computer science. The book’s introductory part provides context to issues in the astronomical sciences that are also important to health, social, and physical sciences, particularly probabilistic and statistical aspects of classification and cluster analysis. The next part describes a number of astrophysics case studies that leverage a range of machine learning and data mining technologies. In the last part, developers of algorithms and practitioners of machine learning and data mining show how these tools and techniques are used in astronomical applications. With contributions from leading astronomers and computer scientists, this book is a practical guide to many of the most important developments in machine learning, data mining, and statistics. It explores how these advances can solve current and future problems in astronomy and looks at how they could lead to the creation of entirely new algorithms within the data mining community.
Advanced Techniques In Knowledge Discovery And Data Mining
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Author : Nikhil Pal
language : en
Publisher: Springer
Release Date : 2014-12-10
Advanced Techniques In Knowledge Discovery And Data Mining written by Nikhil Pal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-10 with Computers categories.
Clear and concise explanations to understand the learning paradigms. Chapters written by leading world experts.
Trends And Applications In Knowledge Discovery And Data Mining
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Author : Mohadeseh Ganji
language : en
Publisher: Springer
Release Date : 2018-12-11
Trends And Applications In Knowledge Discovery And Data Mining written by Mohadeseh Ganji and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-11 with Computers categories.
This book constitutes the thoroughly refereed post-workshop proceedings at PAKDD Workshops 2018, held in conjunction with the 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2018, in Melbourne, Australia, in June 2018. The 32 revised papers presented were carefully reviewed and selected from 46 submissions. The workshops affiliated with PAKDD 2018 include: Workshop on Big Data Analytics for Social Computing, BDASC, Australasian Workshop on Machine Learning for Cyber-security, ML4Cyber, Workshop on Biologically-inspired Techniques for Knowledge Discovery and Data Mining, BDM, Pacific Asia Workshop on Intelligence and Security Informatics, PAISI, and Workshop on Data Mining for Energy Modeling and Optimization, DaMEMO.
Advances In Knowledge Discovery And Data Mining Part I
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Author : Mohammed J. Zaki
language : en
Publisher: Springer
Release Date : 2010-05-29
Advances In Knowledge Discovery And Data Mining Part I written by Mohammed J. Zaki and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-29 with Computers categories.
Annotation This book constitutes the proceedings of the 14th Pacific-Asia Conference, PAKDD 2010, held in Hyderabad, India, in June 2010.
Advances In Data Mining Knowledge Discovery And Applications
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Author : Adem Karahoca
language : en
Publisher: IntechOpen
Release Date : 2012-09-12
Advances In Data Mining Knowledge Discovery And Applications written by Adem Karahoca and has been published by IntechOpen this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-12 with Computers categories.
Advances in Data Mining Knowledge Discovery and Applications aims to help data miners, researchers, scholars, and PhD students who wish to apply data mining techniques. The primary contribution of this book is highlighting frontier fields and implementations of the knowledge discovery and data mining. It seems to be same things are repeated again. But in general, same approach and techniques may help us in different fields and expertise areas. This book presents knowledge discovery and data mining applications in two different sections. As known that, data mining covers areas of statistics, machine learning, data management and databases, pattern recognition, artificial intelligence, and other areas. In this book, most of the areas are covered with different data mining applications. The eighteen chapters have been classified in two parts: Knowledge Discovery and Data Mining Applications.