Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.
Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.
Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.
It contains
Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.
Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
Includes open-access online courses that introduce practical applications of the material in the book
Описание: Algorithms and Applications for Academic Search, Recommendation and Quantitative Association Rule Mining presents novel algorithms for academic search, recommendation and association rule mining that have been developed and optimized for different commercial as well as academic purpose systems. Along with the design and implementation of algorithms, a major part of the work presented in the book involves the development of new systems both for commercial as well as for academic use. In the first part of the book the author introduces a novel hierarchical heuristic scheme for re-ranking academic publications retrieved from standard digital libraries. The scheme is based on the hierarchical combination of a custom implementation of the term frequency heuristic, a time-depreciated citation score and a graph-theoretic computed score that relates the paper’s index terms with each other. In order to evaluate the performance of the introduced algorithms, a meta-search engine has been designed and developed that submits user queries to standard digital repositories of academic publications and re-ranks the top-n results using the introduced hierarchical heuristic scheme. In the second part of the book the design of novel recommendation algorithms with application in different types of e-commerce systems are described. The newly introduced algorithms are a part of a developed Movie Recommendation system, the first such system to be commercially deployed in Greece by a major Triple Play services provider. The initial version of the system uses a novel hybrid recommender (user, item and content based) and provides daily recommendations to all active subscribers of the provider (currently more than 30,000). The recommenders that we are presenting are hybrid by nature, using an ensemble configuration of different content, user as well as item-based recommenders in order to provide more accurate recommendation results.The final part of the book presents the design of a quantitative association rule mining algorithm. Quantitative association rules refer to a special type of association rules of the form that antecedent implies consequent consisting of a set of numerical or quantitative attributes. The introduced mining algorithm processes a specific number of user histories in order to generate a set of association rules with a minimally required support and confidence value. The generated rules show strong relationships that exist between the consequent and the antecedent of each rule, representing different items that have been consumed at specific price levels. This research book will be of appeal to researchers, graduate students, professionals, engineers and computer programmers.
Описание: Big data is a well-trafficked subject in recent IT discourse and does not lack for current research. In fact, there is such a surfeit of material related to big data—and so much of it of questionably reliability, thanks to the high-gloss efforts of savvy tech-marketing gurus—that it can, at times, be difficult for a serious academician to navigate.The Handbook of Research on Trends and Future Directions in Big Data and Web Intelligence cuts through the haze of glitz and pomp surrounding big data and offers a simple, straightforward reference-source of practical academic utility. Covering such topics as cloud computing, parallel computing, natural language processing, and personalized medicine, this volume presents an overview of current research, insight into recent advances, and gaps in the literature indicative of opportunities for future inquiry and is targeted toward a broad, interdisciplinary audience of students, academics, researchers, and professionals in fields of IT, networking, and data-analytics.
Автор: Amanda Spink; Bernard J. Jansen Название: Web Search: Public Searching of the Web ISBN: 9048166292 ISBN-13(EAN): 9789048166299 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book brings together results from the Web search studies we conducted from 1997 through 2004. The aim of our studies has been twofold: to examine how the public at large searches the Web and to highlight trends in public Web searching.
Описание: Focuses on taking advantages from text and web mining in order to address the issues of recommendation and visualization in web searching. The book features coverage of a wide range of topics, such as navigational searching, resource identification, and ambiguous queries.
Автор: Enriquez Raido Название: Translation and Web Searching ISBN: 1138731471 ISBN-13(EAN): 9781138731479 Издательство: Taylor&Francis Рейтинг: Цена: 8114.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents a comprehensive study of various cognitive and affective aspects of web searching for translation problem solving.
Автор: С.Aggarwal Название: Data Mining: The Textbook ISBN: 3319141414 ISBN-13(EAN): 9783319141411 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Поставка под заказ.
Описание: This textbook explores the different aspects of data mining from the fundamentals to the complex data types and their applications, capturing the wide diversity of problem domains for data mining issues.
Автор: Mieczyslaw A. Klopotek; Slawomir T. Wierzchon; Krz Название: Intelligent Information Processing and Web Mining ISBN: 3540250565 ISBN-13(EAN): 9783540250562 Издательство: Springer Рейтинг: Цена: 55762.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Contains articles accepted for presentation during the conference "Intelligent Information Systems 2005 - New Trends in Intelligent Information Processing and Web Mining" held in Poland, in 2005. This book focuses on the developments in the areas of Artificial Immune Systems, Search engines, Computational Linguistics and Knowledge Discovery.
Автор: I-Hsien Ting; Hui-Ju Wu Название: Web Mining Applications in E-Commerce and E-Services ISBN: 3642099866 ISBN-13(EAN): 9783642099861 Издательство: Springer Рейтинг: Цена: 16977.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book offers new developments and high-quality studies into the area of web mining in E-commerce and E-service. It includes chapters on semantic web mining, web performance mining, web mining for social network analysis and for P2P services.
Автор: Mejova Название: Twitter: A Digital Socioscope ISBN: 1107102375 ISBN-13(EAN): 9781107102378 Издательство: Cambridge Academ Рейтинг: Цена: 13462.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book surveys how to use Twitter data to study human behavior and social interaction on a global scale. It is a reference for behavioral and social scientists who want to explore the use of online data in their research, and for non-professionals that follow the social impact of new technologies.
Автор: Guandong Xu; Yanchun Zhang; Lin Li Название: Web Mining and Social Networking ISBN: 1461427185 ISBN-13(EAN): 9781461427186 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book examines the techniques and applications involved in Web mining, Web personalization and recommendation and Web community analysis. It presents in systematic detail the principles, developed algorithms, and research methodologies in these areas.
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