Data Mining IX

Data Mining IX PDF Author: A. Zanasi
Publisher: WIT Press
ISBN: 1845641108
Category : Computers
Languages : en
Pages : 321

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Book Description
Bringing together papers presented at the ninth International Conference on Data Mining, this book addresses the developments in this important field. Featured topics include: data preparation, clustering technologies, customer relationship management, text mining, web mining, and categorisation methods.

Data Mining IX

Data Mining IX PDF Author: A. Zanasi
Publisher: WIT Press
ISBN: 1845641108
Category : Computers
Languages : en
Pages : 321

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Book Description
Bringing together papers presented at the ninth International Conference on Data Mining, this book addresses the developments in this important field. Featured topics include: data preparation, clustering technologies, customer relationship management, text mining, web mining, and categorisation methods.

Data Mining and Machine Learning

Data Mining and Machine Learning PDF Author: Mohammed J. Zaki
Publisher: Cambridge University Press
ISBN: 1108473989
Category : Business & Economics
Languages : en
Pages : 779

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Book Description
New to the second edition of this advanced text are several chapters on regression, including neural networks and deep learning.

Mining of Massive Datasets

Mining of Massive Datasets PDF Author: Jure Leskovec
Publisher: Cambridge University Press
ISBN: 1107077230
Category : Computers
Languages : en
Pages : 480

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Book Description
Now in its second edition, this book focuses on practical algorithms for mining data from even the largest datasets.

Complex Networks IX

Complex Networks IX PDF Author: Sean Cornelius
Publisher: Springer
ISBN: 331973198X
Category : Science
Languages : en
Pages : 341

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Book Description
This book aims to bring together researchers and practitioners working across domains and research disciplines to measure, model, and visualize complex networks. It collects the works presented at the 9th International Conference on Complex Networks (CompleNet) in Boston, MA, March, 2018. With roots in physical, information and social science, the study of complex networks provides a formal set of mathematical methods, computational tools and theories to describe, prescribe and predict dynamics and behaviors of complex systems. Despite their diversity, whether the systems are made up of physical, technological, informational, or social networks, they share many common organizing principles and thus can be studied with similar approaches. This book provides a view of the state-of-the-art in this dynamic field and covers topics such as group decision-making, brain and cellular connectivity, network controllability and resiliency, online activism, recommendation systems, and cyber security.

Handbook of Educational Data Mining

Handbook of Educational Data Mining PDF Author: Cristobal Romero
Publisher: CRC Press
ISBN: 1439804583
Category : Business & Economics
Languages : en
Pages : 528

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Book Description
This handbook provides a thorough overview of the current state of knowledge in this area. The first part of the book includes nine surveys and tutorials on the principal data mining techniques that have been applied in education. The second part presents a set of 25 case studies that give a rich overview of the problems that EDM has addressed. With contributions by well-known researchers from a variety of fields, the book reflects the multidisciplinary nature of the EDM community. It helps education experts understand what types of questions EDM can address and helps data miners understand what types of questions are important to educational design and educational decision making.

Databases and Information Systems IX

Databases and Information Systems IX PDF Author: G. Arnicans
Publisher: IOS Press
ISBN: 1614997144
Category : Computers
Languages : en
Pages : 376

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Book Description
Databases and information systems are now indispensable for the day-to-day functioning of businesses and society. This book presents 25 selected papers from those delivered at the 12th International Baltic Conference on Databases and Information Systems 2016 (DB&IS 2016), held in Riga, Latvia, in July 2016. Since it began in 1994, this biennial conference has become an international forum for researchers and developers in the field of databases, information systems and related areas, and the papers collected here cover a wide spectrum of topics related to the development of information systems and data processing. These include: the development of ontology applications; tools, technologies and languages for model-driven development; decision support systems and data mining; natural language processing and building linguistic components of information systems; advanced systems and technologies related to information systems, databases and information technologies in teaching and learning. The book will be of interest to all those whose work involves the design, application and use of databases and information systems.

Stream Data Mining: Algorithms and Their Probabilistic Properties

Stream Data Mining: Algorithms and Their Probabilistic Properties PDF Author: Leszek Rutkowski
Publisher: Springer
ISBN: 303013962X
Category : Technology & Engineering
Languages : en
Pages : 331

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Book Description
This book presents a unique approach to stream data mining. Unlike the vast majority of previous approaches, which are largely based on heuristics, it highlights methods and algorithms that are mathematically justified. First, it describes how to adapt static decision trees to accommodate data streams; in this regard, new splitting criteria are developed to guarantee that they are asymptotically equivalent to the classical batch tree. Moreover, new decision trees are designed, leading to the original concept of hybrid trees. In turn, nonparametric techniques based on Parzen kernels and orthogonal series are employed to address concept drift in the problem of non-stationary regressions and classification in a time-varying environment. Lastly, an extremely challenging problem that involves designing ensembles and automatically choosing their sizes is described and solved. Given its scope, the book is intended for a professional audience of researchers and practitioners who deal with stream data, e.g. in telecommunication, banking, and sensor networks.

Data Mining and Data Warehousing

Data Mining and Data Warehousing PDF Author: Parteek Bhatia
Publisher: Cambridge University Press
ISBN: 110858585X
Category : Computers
Languages : en
Pages : 514

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Book Description
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, Naïve 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.

Transactions on Rough Sets IX

Transactions on Rough Sets IX PDF Author: Henryk Rybinski
Publisher: Springer
ISBN: 354089876X
Category : Computers
Languages : en
Pages : 760

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Book Description
This book is the ninth volume of the Transactions on Rough Sets series. The 26 papers in it introduce new advances in the foundations and applications of artificial intelligence, engineering, image processing, logic, mathematics, medicine, music, and science.

Clinical Data-Mining

Clinical Data-Mining PDF Author: Irwin Epstein
Publisher: Oxford University Press
ISBN: 019533552X
Category : Computers
Languages : en
Pages : 241

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Book Description
Clinical Data-Mining (CDM) involves the conceptualization, extraction, analysis, and interpretation of available clinical data for practice knowledge-building, clinical decision-making and practitioner reflection. Depending upon the type of data mined, CDM can be qualitative or quantitative; it is generally retrospective, but may be meaningfully combined with original data collection.Any research method that relies on the contents of case records or information systems data inevitably has limitations, but with proper safeguards these can be minimized. Among CDM's strengths however, are that it is unobtrusive, inexpensive, presents little risk to research subjects, and is ethically compatible with practitioner value commitments. When conducted by practitioners, CDM yields conceptual as well as data-driven insight into their own practice- and program-generated questions.This pocket guide, from a seasoned practice-based researcher, covers all the basics of conducting practitioner-initiated CDM studies or CDM doctoral dissertations, drawing extensively on published CDM studies and completed CDM dissertations from multiple social work settings in the United States, Australia, Israel, Hong Kong and the United Kingdom. In addition, it describes consulting principles for researchers interested in forging collaborative university-agency CDM partnerships, making it a practical tool for novice practitioner-researchers and veteran academic-researchers alike.As such, this book is an exceptional guide both for professionals conducting practice-based research as well as for social work faculty seeking an evidence-informed approach to practice-research integration.