Emerging Technologies In Knowledge Discovery And Data Mining
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Emerging Technologies In Knowledge Discovery And Data Mining
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Author : Takashi Washio
language : en
Publisher: Springer
Release Date : 2007-11-27
Emerging Technologies In Knowledge Discovery And Data Mining written by Takashi Washio and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-11-27 with Computers categories.
This book constitutes the thoroughly refereed post-proceedings of three workshops and an industrial track held in conjunction with the 11th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2007, held in Nanjing, China in May 2007. The 62 revised full papers presented together with an overview article to each workshop were carefully reviewed and selected from 355 submissions.
Emerging Technologies In Knowledge Discovery And Data Mining
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Author : Takashi Washio
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-12-14
Emerging Technologies In Knowledge Discovery And Data Mining written by Takashi Washio 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 2007-12-14 with Computers categories.
This book constitutes the thoroughly refereed post-proceedings of three workshops and an industrial track held in conjunction with the 11th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2007, held in Nanjing, China in May 2007. The 62 revised full papers presented together with an overview article to each workshop were carefully reviewed and selected from 355 submissions.
Emerging Technologies In Data Mining And Information Security
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Author : Ajith Abraham
language : en
Publisher: Springer
Release Date : 2018-09-01
Emerging Technologies In Data Mining And Information Security written by Ajith Abraham and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-01 with Technology & Engineering categories.
The book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2018) held at the University of Engineering & Management, Kolkata, India, on February 23–25, 2018. It comprises high-quality research by academics and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers, case studies related to all the areas of data mining, machine learning, IoT and information security.
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.
Emerging Technologies Of Text Mining Techniques And Applications
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Author : do Prado, Hercules Antonio
language : en
Publisher: IGI Global
Release Date : 2007-10-31
Emerging Technologies Of Text Mining Techniques And Applications written by do Prado, Hercules Antonio and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-10-31 with Computers categories.
"This book provides the most recent technical information related to the computational models of the text mining process, discussing techniques within the realms of classification, association analysis, information extraction, and clustering. Offering an innovative approach to the utilization of textual information mining to maximize competitive advantage, it will provide libraries with the defining reference on this topic"--Provided by publisher.
Next Generation Of Data Mining
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Author : Hillol Kargupta
language : en
Publisher: CRC Press
Release Date : 2008-12-24
Next Generation Of Data Mining written by Hillol Kargupta and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-12-24 with Computers categories.
Drawn from the US National Science Foundation's Symposium on Next Generation of Data Mining and Cyber-Enabled Discovery for Innovation (NGDM 07), Next Generation of Data Mining explores emerging technologies and applications in data mining as well as potential challenges faced by the field.Gathering perspectives from top experts across different di
Research And Trends In Data Mining Technologies And Applications
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Author : Taniar, David
language : en
Publisher: IGI Global
Release Date : 2006-10-31
Research And Trends In Data Mining Technologies And Applications written by Taniar, David and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-10-31 with Computers categories.
Activities in data warehousing and mining are constantly emerging. Data mining methods, algorithms, online analytical processes, data mart and practical issues consistently evolve, providing a challenge for professionals in the field. Research and Trends in Data Mining Technologies and Applications focuses on the integration between the fields of data warehousing and data mining, with emphasis on the applicability to real-world problems. This book provides an international perspective, highlighting solutions to some of researchers' toughest challenges. Developments in the knowledge discovery process, data models, structures, and design serve as answers and solutions to these emerging challenges.
Data Mining And Machine Learning Applications
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Author : Rohit Raja
language : en
Publisher: John Wiley & Sons
Release Date : 2022-03-02
Data Mining And Machine Learning Applications written by Rohit Raja and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-02 with Computers categories.
DATA MINING AND MACHINE LEARNING APPLICATIONS The book elaborates in detail on the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines, thus facilitating research development and collaboration. Data, the latest currency of today’s world, is the new gold. In this new form of gold, the most beautiful jewels are data analytics and machine learning. Data mining and machine learning are considered interdisciplinary fields. Data mining is a subset of data analytics and machine learning involves the use of algorithms that automatically improve through experience based on data. Massive datasets can be classified and clustered to obtain accurate results. The most common technologies used include classification and clustering methods. Accuracy and error rates are calculated for regression and classification and clustering to find actual results through algorithms like support vector machines and neural networks with forward and backward propagation. Applications include fraud detection, image processing, medical diagnosis, weather prediction, e-commerce and so forth. The book features: A review of the state-of-the-art in data mining and machine learning, A review and description of the learning methods in human-computer interaction, Implementation strategies and future research directions used to meet the design and application requirements of several modern and real-time applications for a long time, The scope and implementation of a majority of data mining and machine learning strategies. A discussion of real-time problems. Audience Industry and academic researchers, scientists, and engineers in information technology, data science and machine and deep learning, as well as artificial intelligence more broadly.
New Fundamental Technologies In Data Mining
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Author : Kimito Funatsu
language : en
Publisher: BoD – Books on Demand
Release Date : 2011-01-21
New Fundamental Technologies In Data Mining written by Kimito Funatsu and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-21 with Computers categories.
The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by "Data Mining" address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining.
The Handbook Of Emergent Technologies In Social Research
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Author : Sharlene Nagy Hesse-Biber
language : en
Publisher: Oxford University Press
Release Date : 2011-01-15
The Handbook Of Emergent Technologies In Social Research written by Sharlene Nagy Hesse-Biber and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-15 with Social Science categories.
Emergent technologies are pushing the boundaries of how both qualitative and quantitative researchers practice their craft, and it has become clear these changes are dramatically altering research design, from the questions researchers ask and the ways they collect data, to what they even consider data. Gathering a broad range of new developments in one place, The Handbook of Emergent Technologies in Social Research offers comprehensive, up-to-date thinking on technological innovations. In addition to addressing how to effectively apply new technologies-such as the internet, mobile technologies, geospatial technologies (GPS), and the incorporation of computer-assisted software programs (CAQDAS) to qualitative, quantitative, and mixed-methods approaches to research projects-many chapters provide in-depth examples of practices within both disciplinary and interdisciplinary environments and outside the academic world in multi-media laboratories and research institutes. Not only an authoritative view of cutting-edge technologies and their applications, the Handbook examines the costs and benefits of utilizing new technologies on the research process, the potential misuse of these techniques for methods practices, and the ethical and moral dimensions of emergent technologies, especially with regard to issues of surveillance and privacy. The Handbook of Emergent Technologies in Social Research is an essential resource for research methods courses in various fields, including the social sciences, education, communications, computer science, and health services, and an indispensable guide for social researchers looking to incorporate emerging technologies into their methods and practice.