Next Generation Of Data Mining Applications

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Next Generation of Data-Mining Applications

Author : Mehmed Kantardzic
Publisher : Wiley-IEEE Press
ISBN 13 :
Total Pages : 704 pages
Book Rating : 4.:/5 (318 download)

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Book Synopsis Next Generation of Data-Mining Applications by : Mehmed Kantardzic

Download or read book Next Generation of Data-Mining Applications written by Mehmed Kantardzic and published by Wiley-IEEE Press. This book was released on 2005-03-08 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the next generation of data-mining tools and technology This book brings together an international team of eighty experts to present readers with the next generation of data-mining applications. Unlike other publications that take a strictly academic and theoretical approach, this book features authors who have successfully developed data-mining solutions for a variety of customer types. Presenting their state-of-the-art methodologies and techniques, the authors show readers how they can analyze enormous quantities of data and make new discoveries by connecting key pieces of data that may be spread across several different databases and file servers. The latest data-mining techniques that will revolutionize research across a wide variety of fields including business, science, healthcare, and industry are all presented. Organized by application, the twenty-five chapters cover applications in: Industry and business Science and engineering Bioinformatics and biotechnology Medicine and pharmaceuticals Web and text-mining Security New trends in data-mining technology And much more . . . Readers from a variety of disciplines will learn how the next generation of data-mining applications can radically enhance their ability to analyze data and open the doors to new opportunities. Readers will discover: New data-mining tools to automate the evaluation and qualification of sales opportunities The latest tools needed for gene mapping and proteomic data analysis Sophisticated techniques that can be engaged in crime fighting and prevention With its coverage of the most advanced applications, Next Generation of Data-Mining Applications is essential reading for all researchers working in data mining or who are tasked with making sense of an ever-growing quantity of data. The publication also serves as an excellent textbook for upper-level undergraduate and graduate courses in computer science, information management, and statistics.

Next Generation of Data Mining

Author : Hillol Kargupta
Publisher : CRC Press
ISBN 13 : 9781420085877
Total Pages : 601 pages
Book Rating : 4.0/5 (858 download)

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Book Synopsis Next Generation of Data Mining by : Hillol Kargupta

Download or read book Next Generation of Data Mining written by Hillol Kargupta and published by CRC Press. This book was released on 2008-12-24 with total page 601 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 disciplines, the book debates upcoming challenges and outlines computational methods. The contributors look at how ecology, astronomy, social science, medicine, finance, and more can benefit from the next generation of data mining techniques. They examine the algorithms, middleware, infrastructure, and privacy policies associated with ubiquitous, distributed, and high performance data mining. They also discuss the impact of new technologies, such as the semantic web, on data mining and provide recommendations for privacy-preserving mechanisms. The dramatic increase in the availability of massive, complex data from various sources is creating computing, storage, communication, and human-computer interaction challenges for data mining. Providing a framework to better understand these fundamental issues, this volume surveys promising approaches to data mining problems that span an array of disciplines.

Data Mining

Author : Hillol Kargupta
Publisher :
ISBN 13 :
Total Pages : 582 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Data Mining by : Hillol Kargupta

Download or read book Data Mining written by Hillol Kargupta and published by . This book was released on 2004 with total page 582 pages. Available in PDF, EPUB and Kindle. Book excerpt: A state-of-the-art survey of recent advances in data mining or knowledge discovery.

Data Mining for Business Applications

Author : Longbing Cao
Publisher : Springer Science & Business Media
ISBN 13 : 0387794204
Total Pages : 310 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Data Mining for Business Applications by : Longbing Cao

Download or read book Data Mining for Business Applications written by Longbing Cao and published by Springer Science & Business Media. This book was released on 2008-10-03 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining for Business Applications presents the state-of-the-art research and development outcomes on methodologies, techniques, approaches and successful applications in the area. The contributions mark a paradigm shift from “data-centered pattern mining” to “domain driven actionable knowledge discovery” for next-generation KDD research and applications. The contents identify how KDD techniques can better contribute to critical domain problems in theory and practice, and strengthen business intelligence in complex enterprise applications. The volume also explores challenges and directions for future research and development in the dialogue between academia and business.

Practical Applications of Data Mining

Author : Sang Suh
Publisher : Jones & Bartlett Publishers
ISBN 13 : 0763785873
Total Pages : 436 pages
Book Rating : 4.7/5 (637 download)

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Book Synopsis Practical Applications of Data Mining by : Sang Suh

Download or read book Practical Applications of Data Mining written by Sang Suh and published by Jones & Bartlett Publishers. This book was released on 2012 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to data mining -- Association rules -- Classification learning -- Statistics for data mining -- Rough sets and bayes theories -- Neural networks -- Clustering -- Fuzzy information retrieval.

New Fundamental Technologies in Data Mining

Author : Kimito Funatsu
Publisher : BoD – Books on Demand
ISBN 13 : 9533075473
Total Pages : 600 pages
Book Rating : 4.5/5 (33 download)

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Book Synopsis New Fundamental Technologies in Data Mining by : Kimito Funatsu

Download or read book New Fundamental Technologies in Data Mining written by Kimito Funatsu and published by BoD – Books on Demand. This book was released on 2011-01-21 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection

Author : Koyuncugil, Ali Serhan
Publisher : IGI Global
ISBN 13 : 1616928670
Total Pages : 356 pages
Book Rating : 4.6/5 (169 download)

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Book Synopsis Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection by : Koyuncugil, Ali Serhan

Download or read book Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection written by Koyuncugil, Ali Serhan and published by IGI Global. This book was released on 2010-09-30 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection has never been more important, as the research this book presents an alternative to conventional surveillance and risk assessment. This book is a multidisciplinary excursion comprised of data mining, early warning systems, information technologies and risk management and explores the intersection of these components in problematic domains. It offers the ability to apply the most modern techniques to age old problems allowing for increased effectiveness in the response to future, eminent, and present risk.

Advances in Knowledge Discovery and Data Mining

Author : Usama M. Fayyad
Publisher :
ISBN 13 :
Total Pages : 638 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Advances in Knowledge Discovery and Data Mining by : Usama M. Fayyad

Download or read book Advances in Knowledge Discovery and Data Mining written by Usama M. Fayyad and published by . This book was released on 1996 with total page 638 pages. Available in PDF, EPUB and Kindle. Book excerpt: Eight sections of this book span fundamental issues of knowledge discovery, classification and clustering, trend and deviation analysis, dependency derivation, integrated discovery systems, augumented database systems and application case studies. The appendices provide a list of terms used in the literature of the field of data mining and knowledge discovery in databases, and a list of online resources for the KDD researcher.

Advances in Data Mining. Applications and Theoretical Aspects

Author : Petra Perner
Publisher : Springer
ISBN 13 : 3319415611
Total Pages : 446 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Advances in Data Mining. Applications and Theoretical Aspects by : Petra Perner

Download or read book Advances in Data Mining. Applications and Theoretical Aspects written by Petra Perner and published by Springer. This book was released on 2016-06-27 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 16th Industrial Conference on Advances in Data Mining, ICDM 2016, held in New York, NY, USA, in July 2016. The 33 revised full papers presented were carefully reviewed and selected from 100 submissions. The topics range from theoretical aspects of data mining to applications of data mining, such as in multimedia data, in marketing, in medicine, and in process control, industry, and society.

Optimization Based Data Mining: Theory and Applications

Author : Yong Shi
Publisher : Springer Science & Business Media
ISBN 13 : 0857295047
Total Pages : 316 pages
Book Rating : 4.8/5 (572 download)

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Book Synopsis Optimization Based Data Mining: Theory and Applications by : Yong Shi

Download or read book Optimization Based Data Mining: Theory and Applications written by Yong Shi and published by Springer Science & Business Media. This book was released on 2011-05-16 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization techniques have been widely adopted to implement various data mining algorithms. In addition to well-known Support Vector Machines (SVMs) (which are based on quadratic programming), different versions of Multiple Criteria Programming (MCP) have been extensively used in data separations. Since optimization based data mining methods differ from statistics, decision tree induction, and neural networks, their theoretical inspiration has attracted many researchers who are interested in algorithm development of data mining. Optimization based Data Mining: Theory and Applications, mainly focuses on MCP and SVM especially their recent theoretical progress and real-life applications in various fields. These include finance, web services, bio-informatics and petroleum engineering, which has triggered the interest of practitioners who look for new methods to improve the results of data mining for knowledge discovery. Most of the material in this book is directly from the research and application activities that the authors’ research group has conducted over the last ten years. Aimed at practitioners and graduates who have a fundamental knowledge in data mining, it demonstrates the basic concepts and foundations on how to use optimization techniques to deal with data mining problems.

Soft Computing for Data Mining Applications

Author : K. R. Venugopal
Publisher : Springer
ISBN 13 : 3642001939
Total Pages : 341 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Soft Computing for Data Mining Applications by : K. R. Venugopal

Download or read book Soft Computing for Data Mining Applications written by K. R. Venugopal and published by Springer. This book was released on 2009-02-24 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authors have consolidated their research work in this volume titled Soft Computing for Data Mining Applications. The monograph gives an insight into the research in the ?elds of Data Mining in combination with Soft Computing methodologies. In these days, the data continues to grow - ponentially. Much of the data is implicitly or explicitly imprecise. Database discovery seeks to discover noteworthy, unrecognized associations between the data items in the existing database. The potential of discovery comes from the realization that alternate contexts may reveal additional valuable information. The rate at which the data is storedis growing at a phenomenal rate. Asaresult,traditionaladhocmixturesofstatisticaltechniquesanddata managementtools are no longer adequate for analyzing this vast collection of data. Severaldomainswherelargevolumesofdataarestoredincentralizedor distributeddatabasesincludesapplicationslikeinelectroniccommerce,bio- formatics, computer security, Web intelligence, intelligent learning database systems,?nance,marketing,healthcare,telecommunications,andother?elds. E?cient tools and algorithms for knowledge discovery in large data sets have been devised during the recent years. These methods exploit the ca- bility of computers to search huge amounts of data in a fast and e?ective manner. However,the data to be analyzed is imprecise and a?icted with - certainty. In the case of heterogeneous data sources such as text and video, the data might moreover be ambiguous and partly con?icting. Besides, p- terns and relationships of interest are usually approximate. Thus, in order to make the information mining process more robust it requires tolerance toward imprecision, uncertainty and exceptions.

Machine Learning and Data Mining for Computer Security

Author : Marcus A. Maloof
Publisher : Springer Science & Business Media
ISBN 13 : 1846282535
Total Pages : 218 pages
Book Rating : 4.8/5 (462 download)

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Book Synopsis Machine Learning and Data Mining for Computer Security by : Marcus A. Maloof

Download or read book Machine Learning and Data Mining for Computer Security written by Marcus A. Maloof and published by Springer Science & Business Media. This book was released on 2006-02-27 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Machine Learning and Data Mining for Computer Security" provides an overview of the current state of research in machine learning and data mining as it applies to problems in computer security. This book has a strong focus on information processing and combines and extends results from computer security. The first part of the book surveys the data sources, the learning and mining methods, evaluation methodologies, and past work relevant for computer security. The second part of the book consists of articles written by the top researchers working in this area. These articles deals with topics of host-based intrusion detection through the analysis of audit trails, of command sequences and of system calls as well as network intrusion detection through the analysis of TCP packets and the detection of malicious executables. This book fills the great need for a book that collects and frames work on developing and applying methods from machine learning and data mining to problems in computer security.

Next Generation Data Technologies for Collective Computational Intelligence

Author : Nik Bessis
Publisher : Springer
ISBN 13 : 3642203442
Total Pages : 638 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Next Generation Data Technologies for Collective Computational Intelligence by : Nik Bessis

Download or read book Next Generation Data Technologies for Collective Computational Intelligence written by Nik Bessis and published by Springer. This book was released on 2011-06-29 with total page 638 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on next generation data technologies in support of collective and computational intelligence. The book brings various next generation data technologies together to capture, integrate, analyze, mine, annotate and visualize distributed data – made available from various community users – in a meaningful and collaborative for the organization manner. A unique perspective on collective computational intelligence is offered by embracing both theory and strategies fundamentals such as data clustering, graph partitioning, collaborative decision making, self-adaptive ant colony, swarm and evolutionary agents. It also covers emerging and next generation technologies in support of collective computational intelligence such as Web 2.0 social networks, semantic web for data annotation, knowledge representation and inference, data privacy and security, and enabling distributed and collaborative paradigms such as P2P, Grid and Cloud Computing due to the geographically dispersed and distributed nature of the data. The book aims to cover in a comprehensive manner the combinatorial effort of utilizing and integrating various next generations collaborative and distributed data technologies for computational intelligence in various scenarios. The book also distinguishes itself by assessing whether utilization and integration of next generation data technologies can assist in the identification of new opportunities, which may also be strategically fit for purpose.

Data Mining for Business Analytics

Author : Galit Shmueli
Publisher : John Wiley & Sons
ISBN 13 : 1119549841
Total Pages : 610 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis Data Mining for Business Analytics by : Galit Shmueli

Download or read book Data Mining for Business Analytics written by Galit Shmueli and published by John Wiley & Sons. This book was released on 2019-11-05 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems and opportunities. This is the sixth version of this successful text, and the first using Python. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: A new co-author, Peter Gedeck, who brings both experience teaching business analytics courses using Python, and expertise in the application of machine learning methods to the drug-discovery process A new section on ethical issues in data mining Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology. “This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.” —Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R

Artificial Intelligence in Data Mining

Author : D. Binu
Publisher : Academic Press
ISBN 13 : 0128206160
Total Pages : 270 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Artificial Intelligence in Data Mining by : D. Binu

Download or read book Artificial Intelligence in Data Mining written by D. Binu and published by Academic Press. This book was released on 2021-02-17 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Developing Multi-Database Mining Applications

Author : Animesh Adhikari
Publisher : Springer Science & Business Media
ISBN 13 : 1849960445
Total Pages : 134 pages
Book Rating : 4.8/5 (499 download)

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Book Synopsis Developing Multi-Database Mining Applications by : Animesh Adhikari

Download or read book Developing Multi-Database Mining Applications written by Animesh Adhikari and published by Springer Science & Business Media. This book was released on 2010-06-14 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-database mining has been recognized recently as an important and strategically essential area of research in data mining. In this book, we discuss various issues regarding the systematic and efficient development of multi-database mining applications. It explains how systematically one could prepare data warehouses at different branches. As appropriate multi-database mining technique is essential to develop better applications. Also, the efficiency of a multi-database mining application could be improved by processing more patterns in the application. A faster algorithm could also play an important role in developing a better application. Thus the efficiency of a multi-database mining application could be enhanced by choosing an appropriate multi-database mining model, an appropriate pattern synthesizing technique, a better pattern representation technique, and an efficient algorithm for solving the problem. This book illustrates each of these issues either in the context of a specific problem, or in general.

Domain Driven Data Mining

Author : Longbing Cao
Publisher : Springer Science & Business Media
ISBN 13 : 1441957375
Total Pages : 251 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Domain Driven Data Mining by : Longbing Cao

Download or read book Domain Driven Data Mining written by Longbing Cao and published by Springer Science & Business Media. This book was released on 2010-01-08 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers state-of the-art research and development outcomes on methodologies, techniques, approaches and successful applications in domain driven, actionable knowledge discovery. It bridges the gap between business expectations and research output.