[PDF] Computational Intelligence In Data Mining Volume 2 - eBooks Review

Computational Intelligence In Data Mining Volume 2


Computational Intelligence In Data Mining Volume 2
DOWNLOAD

Download Computational Intelligence In Data Mining Volume 2 PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Computational Intelligence In Data Mining Volume 2 book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page



Computational Intelligence In Data Mining Volume 2


Computational Intelligence In Data Mining Volume 2
DOWNLOAD
Author : Himansu Sekhar Behera
language : en
Publisher: Springer
Release Date : 2015-12-09

Computational Intelligence In Data Mining Volume 2 written by Himansu Sekhar Behera and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-09 with Technology & Engineering categories.


The book is a collection of high-quality peer-reviewed research papers presented in the Second International Conference on Computational Intelligence in Data Mining (ICCIDM 2015) held at Bhubaneswar, Odisha, India during 5 – 6 December 2015. The two-volume Proceedings address the difficulties and challenges for the seamless integration of two core disciplines of computer science, i.e., computational intelligence and data mining. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.



Computational Intelligence In Data Mining Volume 2


Computational Intelligence In Data Mining Volume 2
DOWNLOAD
Author : Lakhmi C. Jain
language : en
Publisher: Springer
Release Date : 2014-12-10

Computational Intelligence In Data Mining Volume 2 written by Lakhmi C. Jain 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 Technology & Engineering categories.


The contributed volume aims to explicate and address the difficulties and challenges that of seamless integration of the two core disciplines of computer science, i.e., computational intelligence and data mining. Data Mining aims at the automatic discovery of underlying non-trivial knowledge from datasets by applying intelligent analysis techniques. The interest in this research area has experienced a considerable growth in the last years due to two key factors: (a) knowledge hidden in organizations’ databases can be exploited to improve strategic and managerial decision-making; (b) the large volume of data managed by organizations makes it impossible to carry out a manual analysis. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.



Computational Intelligence In Data Mining


Computational Intelligence In Data Mining
DOWNLOAD
Author : Giacomo Della Riccia
language : en
Publisher: Springer
Release Date : 2014-05-04

Computational Intelligence In Data Mining written by Giacomo Della Riccia and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-04 with Computers categories.


The book aims to merge Computational Intelligence with Data Mining, which are both hot topics of current research and industrial development, Computational Intelligence, incorporates techniques like data fusion, uncertain reasoning, heuristic search, learning, and soft computing. Data Mining focuses on unscrambling unknown patterns or structures in very large data sets. Under the headline "Discovering Structures in Large Databases” the book starts with a unified view on ‘Data Mining and Statistics – A System Point of View’. Two special techniques follow: ‘Subgroup Mining’, and ‘Data Mining with Possibilistic Graphical Models’. "Data Fusion and Possibilistic or Fuzzy Data Analysis” is the next area of interest. An overview of possibilistic logic, nonmonotonic reasoning and data fusion is given, the coherence problem between data and non-linear fuzzy models is tackled, and outlier detection based on learning of fuzzy models is studied. In the domain of "Classification and Decomposition” adaptive clustering and visualisation of high dimensional data sets is introduced. Finally, in the section "Learning and Data Fusion” learning of special multi-agents of virtual soccer is considered. The last topic is on data fusion based on stochastic models.



Computational Intelligence In Data Mining


Computational Intelligence In Data Mining
DOWNLOAD
Author : Himansu Sekhar Behera
language : en
Publisher: Springer
Release Date : 2019-08-17

Computational Intelligence In Data Mining written by Himansu Sekhar Behera and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-17 with Technology & Engineering categories.


This proceeding discuss the latest solutions, scientific findings and methods for solving intriguing problems in the fields of data mining, computational intelligence, big data analytics, and soft computing. This gathers outstanding papers from the fifth International Conference on “Computational Intelligence in Data Mining” (ICCIDM), and offer a “sneak preview” of the strengths and weaknesses of trending applications, together with exciting advances in computational intelligence, data mining, and related fields.



Computational Intelligence In Data Mining


Computational Intelligence In Data Mining
DOWNLOAD
Author : Himansu Sekhar Behera
language : en
Publisher: Springer
Release Date : 2017-05-19

Computational Intelligence In Data Mining written by Himansu Sekhar Behera and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-19 with Technology & Engineering categories.


The book presents high quality papers presented at the International Conference on Computational Intelligence in Data Mining (ICCIDM 2016) organized by School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha, India during December 10 – 11, 2016. The book disseminates the knowledge about innovative, active research directions in the field of data mining, machine and computational intelligence, along with current issues and applications of related topics. The volume aims to explicate and address the difficulties and challenges that of seamless integration of the two core disciplines of computer science.



Artificial Intelligence And Data Mining For Mergers And Acquisitions


Artificial Intelligence And Data Mining For Mergers And Acquisitions
DOWNLOAD
Author : Debasis Chanda
language : en
Publisher: CRC Press
Release Date : 2021-03-18

Artificial Intelligence And Data Mining For Mergers And Acquisitions written by Debasis Chanda and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-18 with Business & Economics categories.


The goal of this book is to present a modeling framework for the Virtual Organization that is focused on process composition. This framework uses Predicate Calculus Knowledge Bases. Petri Net-based modeling is also discussed. In this context, a Data Mining model is proposed, using a fuzzy mathematical approach, aiming to discover knowledge. A Knowledge-Based framework has been proposed in order to present an all-inclusive knowledge store for static and dynamic properties. Toward this direction, a Knowledge Base is created, and inferences are arrived at. This book features an advisory tool for Mergers and Acquisitions of Organizations using the Fuzzy Data Mining Framework and highlights the novelty of a Knowledge-Based Service-Oriented Architecture approach and development of an Enterprise Architectural model using AI that serves a wide audience. Students of Strategic Management in business schools and postgraduate programs in technology institutes seeking application areas of AI and Data Mining, as well as business/technology professionals in organizations aiming to create value through Mergers and Acquisitions and elsewhere, will benefit from the reading of this book.



Computational Intelligence In Data Mining Volume 1


Computational Intelligence In Data Mining Volume 1
DOWNLOAD
Author : Himansu Sekhar Behera
language : en
Publisher: Springer
Release Date : 2015-12-08

Computational Intelligence In Data Mining Volume 1 written by Himansu Sekhar Behera and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-08 with Technology & Engineering categories.


The book is a collection of high-quality peer-reviewed research papers presented in the Second International Conference on Computational Intelligence in Data Mining (ICCIDM 2015) held at Bhubaneswar, Odisha, India during 5 – 6 December 2015. The two-volume Proceedings address the difficulties and challenges for the seamless integration of two core disciplines of computer science, i.e., computational intelligence and data mining. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.



Computational Intelligence In Data Mining Volume 3


Computational Intelligence In Data Mining Volume 3
DOWNLOAD
Author : Lakhmi C. Jain
language : en
Publisher: Springer
Release Date : 2014-12-11

Computational Intelligence In Data Mining Volume 3 written by Lakhmi C. Jain and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-11 with Technology & Engineering categories.


The contributed volume aims to explicate and address the difficulties and challenges for the seamless integration of two core disciplines of computer science, i.e., computational intelligence and data mining. Data Mining aims at the automatic discovery of underlying non-trivial knowledge from datasets by applying intelligent analysis techniques. The interest in this research area has experienced a considerable growth in the last years due to two key factors: (a) knowledge hidden in organizations’ databases can be exploited to improve strategic and managerial decision-making; (b) the large volume of data managed by organizations makes it impossible to carry out a manual analysis. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.



Pocket Data Mining


Pocket Data Mining
DOWNLOAD
Author : Mohamed Medhat Gaber
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-10-19

Pocket Data Mining written by Mohamed Medhat Gaber 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 2013-10-19 with Technology & Engineering categories.


Owing to continuous advances in the computational power of handheld devices like smartphones and tablet computers, it has become possible to perform Big Data operations including modern data mining processes onboard these small devices. A decade of research has proved the feasibility of what has been termed as Mobile Data Mining, with a focus on one mobile device running data mining processes. However, it is not before 2010 until the authors of this book initiated the Pocket Data Mining (PDM) project exploiting the seamless communication among handheld devices performing data analysis tasks that were infeasible until recently. PDM is the process of collaboratively extracting knowledge from distributed data streams in a mobile computing environment. This book provides the reader with an in-depth treatment on this emerging area of research. Details of techniques used and thorough experimental studies are given. More importantly and exclusive to this book, the authors provide detailed practical guide on the deployment of PDM in the mobile environment. An important extension to the basic implementation of PDM dealing with concept drift is also reported. In the era of Big Data, potential applications of paramount importance offered by PDM in a variety of domains including security, business and telemedicine are discussed.



Artificial Intelligence In Data Mining


Artificial Intelligence In Data Mining
DOWNLOAD
Author : D. Binu
language : en
Publisher: Academic Press
Release Date : 2021-02-17

Artificial Intelligence In Data Mining written by D. Binu and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-17 with Science categories.


Artificial Intelligence in Data Mining: Theories and Applications offers a comprehensive introduction to data mining theories, relevant AI techniques, and their many real-world applications. This book is written by experienced engineers for engineers, biomedical engineers, and researchers in neural networks, as well as computer scientists with an interest in the area. - Provides coverage of the fundamentals of Artificial Intelligence as applied to data mining, including computational intelligence and unsupervised learning methods for data clustering - Presents coverage of key topics such as heuristic methods for data clustering, deep learning methods for data classification, and neural networks - Includes case studies and real-world applications of AI techniques in data mining, for improved outcomes in clinical diagnosis, satellite data extraction, agriculture, security and defense