ZHENGXIN CHEN is Professor in the Department of Computer Science at the University of Nebraska.
An expert guide for applying data mining with uncertain reasoning to a wide range of usesThis volume presents a holistic view of data mining by integrating this diverse and exciting field with uncertain reasoning. It treats a wide range of issues and examines the state of the art in both fields while summarizing vital concepts that can normally only be found in various separate resources.The author concentrates on practical aspects of data mining-such as infrastructure and overall processes-but also discusses some selected algorithms and performance-related issues. Several important topics are addressed specifically, such as bridging the fields of machine learning and data mining and the discovery of influential association rules. In addition, the author discusses data warehousing as an enabling technique for data mining. Case studies are included throughout to illustrate important concepts.Data Mining and Uncertain Reasoning is a practical reference for practitioners in various interrelated fields. Each subject is treated with both basic introductory and advanced technical deillegalscriptions, making the book suitable for students and practitioners at various levels of experience.|Dieses Buch behandelt die Theorie der unscharfen Folgerungen (uncertain reasoning) im Zusammenhang mit Data Mining, die anhand einer Reihe vollständiger Fallstudien anschaulich erläutert wird. Eine große Auswahl von Zusatzliteratur rundet das Bild ab.
This book explores the two fields of uncertain reasoning and data mining and discusses applications for using both in concert. The author uses an integrated approach to present fully developed applications in a variety of areas.
Dieses Buch behandelt die Theorie der unscharfen Folgerungen (uncertain reasoning) im Zusammenhang mit Data Mining, die anhand einer Reihe vollständiger Fallstudien anschaulich erläutert wird. Eine große Auswahl von Zusatzliteratur rundet das Bild ab.
What This Book Is About.
Basics of Data Mining.
Enabling Techniques and Advanced Features of Data Mining.
Dealing with Uncertainty in Manipulation of Data.
Data Mining Tasks for Knowledge Discovery.
Bayesian Networks and Artificial Neural Networks.
Uncertain Reasoning Techniques for Data Mining.
Data Mining Lifecycle with Uncertainty Handling: Case Studies and Software Tools.
Intelligent Conceptual Query Answering with Uncertainty: Basic Aspects and Case Studies.
References.
Index.
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Über den Autor
ZHENGXIN CHEN is Professor in the Department of Computer Science at the University of Nebraska.
Inhaltsverzeichnis
What This Book Is About.
Basics of Data Mining.
Enabling Techniques and Advanced Features of Data Mining.
Dealing with Uncertainty in Manipulation of Data.
Data Mining Tasks for Knowledge Discovery.
Bayesian Networks and Artificial Neural Networks.
Uncertain Reasoning Techniques for Data Mining.
Data Mining Lifecycle with Uncertainty Handling: Case Studies and Software Tools.
Intelligent Conceptual Query Answering with Uncertainty: Basic Aspects and Case Studies.
References.
Index.
Klappentext
Dieses Buch behandelt die Theorie der unscharfen Folgerungen (uncertain reasoning) im Zusammenhang mit Data Mining, die anhand einer Reihe vollständiger Fallstudien anschaulich erläutert wird. Eine große Auswahl von Zusatzliteratur rundet das Bild ab.
