Focusing Solutions for Data Mining

Focusing Solutions for Data Mining PDF Author: Thomas Reinartz
Publisher: Springer
ISBN: 3540483160
Category : Computers
Languages : en
Pages : 317

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Book Description
In the first part, this book analyzes the knowledge discovery process in order to understand the relations between knowledge discovery steps and focusing. The part devoted to the development of focusing solutions opens with an analysis of the state of the art, then introduces the relevant techniques, and finally culminates in implementing a unified approach as a generic sampling algorithm, which is then integrated into a commercial data mining system. The last part evaluates specific focusing solutions in various application domains. The book provides various appendicies enhancing easy accessibility. The book presents a comprehensive introduction to focusing in the context of data mining and knowledge discovery. It is written for researchers and advanced students, as well as for professionals applying data mining and knowledge discovery techniques in practice.

Focusing Solutions for Data Mining

Focusing Solutions for Data Mining PDF Author: Thomas Reinartz
Publisher: Springer
ISBN: 3540483160
Category : Computers
Languages : en
Pages : 317

Get Book Here

Book Description
In the first part, this book analyzes the knowledge discovery process in order to understand the relations between knowledge discovery steps and focusing. The part devoted to the development of focusing solutions opens with an analysis of the state of the art, then introduces the relevant techniques, and finally culminates in implementing a unified approach as a generic sampling algorithm, which is then integrated into a commercial data mining system. The last part evaluates specific focusing solutions in various application domains. The book provides various appendicies enhancing easy accessibility. The book presents a comprehensive introduction to focusing in the context of data mining and knowledge discovery. It is written for researchers and advanced students, as well as for professionals applying data mining and knowledge discovery techniques in practice.

Instance Selection and Construction for Data Mining

Instance Selection and Construction for Data Mining PDF Author: Huan Liu
Publisher: Springer Science & Business Media
ISBN: 1475733593
Category : Computers
Languages : en
Pages : 433

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Book Description
The ability to analyze and understand massive data sets lags far behind the ability to gather and store the data. To meet this challenge, knowledge discovery and data mining (KDD) is growing rapidly as an emerging field. However, no matter how powerful computers are now or will be in the future, KDD researchers and practitioners must consider how to manage ever-growing data which is, ironically, due to the extensive use of computers and ease of data collection with computers. Many different approaches have been used to address the data explosion issue, such as algorithm scale-up and data reduction. Instance, example, or tuple selection pertains to methods or algorithms that select or search for a representative portion of data that can fulfill a KDD task as if the whole data is used. Instance selection is directly related to data reduction and becomes increasingly important in many KDD applications due to the need for processing efficiency and/or storage efficiency. One of the major means of instance selection is sampling whereby a sample is selected for testing and analysis, and randomness is a key element in the process. Instance selection also covers methods that require search. Examples can be found in density estimation (finding the representative instances - data points - for a cluster); boundary hunting (finding the critical instances to form boundaries to differentiate data points of different classes); and data squashing (producing weighted new data with equivalent sufficient statistics). Other important issues related to instance selection extend to unwanted precision, focusing, concept drifts, noise/outlier removal, data smoothing, etc. Instance Selection and Construction for Data Mining brings researchers and practitioners together to report new developments and applications, to share hard-learned experiences in order to avoid similar pitfalls, and to shed light on the future development of instance selection. This volume serves as a comprehensive reference for graduate students, practitioners and researchers in KDD.

Focusing Solutions for Data Mining

Focusing Solutions for Data Mining PDF Author: Thomas Reinartz
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Book Description


Knowledge Discovery and Data Mining: Challenges and Realities

Knowledge Discovery and Data Mining: Challenges and Realities PDF Author: Zhu, Xingquan
Publisher: IGI Global
ISBN: 1599042541
Category : Computers
Languages : en
Pages : 290

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Book Description
"This book provides a focal point for research and real-world data mining practitioners that advance knowledge discovery from low-quality data; it presents in-depth experiences and methodologies, providing theoretical and empirical guidance to users who have suffered from underlying low-quality data. Contributions also focus on interdisciplinary collaborations among data quality, data processing, data mining, data privacy, and data sharing"--Provided by publisher.

Advances in Data Mining. Applications and Theoretical Aspects

Advances in Data Mining. Applications and Theoretical Aspects PDF Author: Petra Perner
Publisher: Springer
ISBN: 3642314880
Category : Computers
Languages : en
Pages : 299

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Book Description
This book constitutes the refereed proceedings of the 12th Industrial Conference on Data Mining, ICDM 2012, held in Berlin, Germany in July 2012. The 22 revised full papers presented were carefully reviewed and selected from 97 submissions. The papers are organized in topical sections on data mining in medicine and biology; data mining for energy industry; data mining in traffic and logistic; data mining in telecommunication; data mining in engineering; theory in data mining; theory in data mining: clustering; theory in data mining: association rule mining and decision rule mining.

Integration of Data Mining in Business Intelligence Systems

Integration of Data Mining in Business Intelligence Systems PDF Author: Azevedo, Ana
Publisher: IGI Global
ISBN: 1466664789
Category : Computers
Languages : en
Pages : 340

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Book Description
Uncovering and analyzing data associated with the current business environment is essential in maintaining a competitive edge. As such, making informed decisions based on this data is crucial to managers across industries. Integration of Data Mining in Business Intelligence Systems investigates the incorporation of data mining into business technologies used in the decision making process. Emphasizing cutting-edge research and relevant concepts in data discovery and analysis, this book is a comprehensive reference source for policymakers, academicians, researchers, students, technology developers, and professionals interested in the application of data mining techniques and practices in business information systems.

Business Intelligence and Agile Methodologies for Knowledge-Based Organizations: Cross-Disciplinary Applications

Business Intelligence and Agile Methodologies for Knowledge-Based Organizations: Cross-Disciplinary Applications PDF Author: Rahman El Sheikh, Asim Abdel
Publisher: IGI Global
ISBN: 1613500513
Category : Computers
Languages : en
Pages : 370

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Book Description
Business intelligence applications are of vital importance as they help organizations manage, develop, and communicate intangible assets such as information and knowledge. Organizations that have undertaken business intelligence initiatives have benefited from increases in revenue, as well as significant cost savings.Business Intelligence and Agile Methodologies for Knowledge-Based Organizations: Cross-Disciplinary Applications highlights the marriage between business intelligence and knowledge management through the use of agile methodologies. Through its fifteen chapters, this book offers perspectives on the integration between process modeling, agile methodologies, business intelligence, knowledge management, and strategic management.

Data Mining for Design and Manufacturing

Data Mining for Design and Manufacturing PDF Author: D. Braha
Publisher: Springer Science & Business Media
ISBN: 1475749112
Category : Computers
Languages : en
Pages : 530

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Book Description
Data Mining for Design and Manufacturing: Methods and Applications is the first book that brings together research and applications for data mining within design and manufacturing. The aim of the book is 1) to clarify the integration of data mining in engineering design and manufacturing, 2) to present a wide range of domains to which data mining can be applied, 3) to demonstrate the essential need for symbiotic collaboration of expertise in design and manufacturing, data mining, and information technology, and 4) to illustrate how to overcome central problems in design and manufacturing environments. The book also presents formal tools required to extract valuable information from design and manufacturing data, and facilitates interdisciplinary problem solving for enhanced decision making. Audience: The book is aimed at both academic and practising audiences. It can serve as a reference or textbook for senior or graduate level students in Engineering, Computer, and Management Sciences who are interested in data mining technologies. The book will be useful for practitioners interested in utilizing data mining techniques in design and manufacturing as well as for computer software developers engaged in developing data mining tools.

Signal

Signal PDF Author:
Publisher:
ISBN:
Category : Armed Forces
Languages : en
Pages : 776

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Book Description


Data Mining

Data Mining PDF Author: Robert Groth
Publisher: Prentice Hall
ISBN:
Category : Business & Economics
Languages : en
Pages : 312

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Book Description
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