Data Mining and Analysis

Fundamental Concepts and Algorithms

Author: Mohammed J. Zaki,Wagner Meira, Jr

Publisher: Cambridge University Press

ISBN: 0521766338

Category: Computers

Page: 562

View: 476

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A comprehensive overview of data mining from an algorithmic perspective, integrating related concepts from machine learning and statistics.

Machine Learning and Data Mining in Pattern Recognition

13th International Conference, MLDM 2017, New York, NY, USA, July 15-20, 2017, Proceedings

Author: Petra Perner

Publisher: Springer

ISBN: 3319624164

Category: Computers

Page: 452

View: 505

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This book constitutes the refereed proceedings of the 13th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2017, held in New York, NY, USA in July/August 2017.The 31 full papers presented in this book were carefully reviewed and selected from 150 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.

Data Mining Technique: Fundamental Concept and Statistical Analysis

Author: Dr. Sagar S. Jambhorkar & Mr. Vijay S. Jondhale

Publisher: Horizon Books ( A Division of Ignited Minds Edutech P Ltd)

ISBN: 9384044962

Category:

Page: 119

View: 512

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Data Mining and Data Warehousing is the recent trend in IT field but still it is widely used in various areas. This book introduces basic as well as advanced techniques of data mining & brief information about data warehousing. The book also contains some advanced software tools which are really helpful for students. In this book I tried to explain all the techniques and concepts of the data mining & data warehousing, in very simplified & descriptive way which can help to the student for there examination preparation as well as technical improvement.

Advances in Data Mining: Applications and Theoretical Aspects

15th Industrial Conference, ICDM 2015, Hamburg, Germany, July 11–24, 2015. Proceedings

Author: Petra Perner

Publisher: Springer

ISBN: 3319209108

Category: Computers

Page: 279

View: 5957

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This book constitutes the refereed proceedings of the 15th Industrial Conference on Advances in Data Mining, ICDM 2015, held in Hamburg, Germany, in July 2015. The 16 revised full papers presented were carefully reviewed and selected from numerous 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 agriculture, and in process control, industry and society.

Social Media Mining

An Introduction

Author: Reza Zafarani,Mohammad Ali Abbasi,Huan Liu

Publisher: Cambridge University Press

ISBN: 1139916122

Category: Computers

Page: N.A

View: 5211

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The growth of social media over the last decade has revolutionized the way individuals interact and industries conduct business. Individuals produce data at an unprecedented rate by interacting, sharing, and consuming content through social media. Understanding and processing this new type of data to glean actionable patterns presents challenges and opportunities for interdisciplinary research, novel algorithms and tool development. Social Media Mining integrates social media, social network analysis, and data mining to provide a coherent platform to understand the basics and potentials of social media mining. It introduces the unique problems arising from social media data and presents fundamental concepts, emerging issues, and effective algorithms for network analysis and data mining. Suitable for use in advanced undergraduate and beginning graduate courses as well as professional short courses, the text contains exercises of different degrees of difficulty that improve understanding and help apply concepts, principles and methods for social media mining.

Data Mining and Data Warehousing

Principles and Practical Techniques

Author: Parteek Bhatia

Publisher: Cambridge University Press

ISBN: 1108727743

Category: Computers

Page: 600

View: 1632

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Written in lucid language, this valuable textbook brings together fundamental concepts of data mining and data warehousing in a single volume. Important topics including information theory, decision tree, Nave Bayes classifier, distance metrics, partitioning clustering, associate mining, data marts and operational data store are discussed comprehensively. The textbook is written to cater to the needs of undergraduate students of computer science, engineering and information technology for a course on data mining and data warehousing. The text simplifies the understanding of the concepts through exercises and practical examples. Chapters such as classification, associate mining and cluster analysis are discussed in detail with their practical implementation using Weka and R language data mining tools. Advanced topics including big data analytics, relational data models and NoSQL are discussed in detail. Pedagogical features including unsolved problems and multiple-choice questions are interspersed throughout the book for better understanding.

Introduction to Data Mining

Author: Pang-Ning Tan,Michael Steinbach,Anuj Karpatne,Vipin Kumar

Publisher: Addison-Wesley

ISBN: 9780133128901

Category: Computers

Page: 864

View: 8911

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Introducing the fundamental concepts and algorithms of data mining Introduction to Data Mining, 2nd Edition , gives a comprehensive overview of the background and general themes of data mining and is designed to be useful to students, instructors, researchers, and professionals. Presented in a clear and accessible way, the book outlines fundamental concepts and algorithms for each topic, thus providing the reader with the necessary background for the application of data mining to real problems. The text helps readers understand the nuances of the subject, and includes important sections on classification, association analysis, and cluster analysis. This edition improves on the first iteration of the book, published over a decade ago, by addressing the significant changes in the industry as a result of advanced technology and data growth.

Contrast Data Mining

Concepts, Algorithms, and Applications

Author: Guozhu Dong,James Bailey

Publisher: CRC Press

ISBN: 1439854335

Category: Business & Economics

Page: 434

View: 9375

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A Fruitful Field for Researching Data Mining Methodology and for Solving Real-Life Problems Contrast Data Mining: Concepts, Algorithms, and Applications collects recent results from this specialized area of data mining that have previously been scattered in the literature, making them more accessible to researchers and developers in data mining and other fields. The book not only presents concepts and techniques for contrast data mining, but also explores the use of contrast mining to solve challenging problems in various scientific, medical, and business domains. Learn from Real Case Studies of Contrast Mining Applications In this volume, researchers from around the world specializing in architecture engineering, bioinformatics, computer science, medicine, and systems engineering focus on the mining and use of contrast patterns. They demonstrate many useful and powerful capabilities of a variety of contrast mining techniques and algorithms, including tree-based structures, zero-suppressed binary decision diagrams, data cube representations, and clustering algorithms. They also examine how contrast mining is used in leukemia characterization, discriminative gene transfer and microarray analysis, computational toxicology, spatial and image data classification, voting analysis, heart disease prediction, crime analysis, understanding customer behavior, genetic algorithms, and network security.

Data Mining

Concepts, Models, Methods, and Algorithms

Author: Mehmed Kantardzic

Publisher: John Wiley & Sons

ISBN: 0470890452

Category: Computers

Page: 480

View: 9281

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This book reviews state-of-the-art methodologies and techniques for analyzing enormous quantities of raw data in high-dimensional data spaces, to extract new information for decision making. The goal of this book is to provide a single introductory source, organized in a systematic way, in which we could direct the readers in analysis of large data sets, through the explanation of basic concepts, models and methodologies developed in recent decades.

Advanced Data Mining Techniques

Author: David L. Olson,Dursun Delen

Publisher: Springer Science & Business Media

ISBN: 9783540769170

Category: Business & Economics

Page: 180

View: 6613

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This book covers the fundamental concepts of data mining, to demonstrate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. The book is organized in three parts. Part I introduces concepts. Part II describes and demonstrates basic data mining algorithms. It also contains chapters on a number of different techniques often used in data mining. Part III focuses on business applications of data mining.