Author: Petra Perner
Publisher: Springer Science & Business Media
ISBN: 3642143997
Category : Computers
Languages : en
Pages : 667
Book Description
These are the proceedings of the tenth event of the Industrial Conference on Data Mining ICDM held in Berlin (www.data-mining-forum.de). For this edition the Program Committee received 175 submissions. After the pe- review process, we accepted 49 high-quality papers for oral presentation that are included in this book. The topics range from theoretical aspects of data mining to app- cations of data mining such as on multimedia data, in marketing, finance and telec- munication, in medicine and agriculture, and in process control, industry and society. Extended versions of selected papers will appear in the international journal Trans- tions on Machine Learning and Data Mining (www.ibai-publishing.org/journal/mldm). Ten papers were selected for poster presentations and are published in the ICDM Poster Proceeding Volume by ibai-publishing (www.ibai-publishing.org). In conjunction with ICDM four workshops were held on special hot applicati- oriented topics in data mining: Data Mining in Marketing DMM, Data Mining in LifeScience DMLS, the Workshop on Case-Based Reasoning for Multimedia Data CBR-MD, and the Workshop on Data Mining in Agriculture DMA. The Workshop on Data Mining in Agriculture ran for the first time this year. All workshop papers will be published in the workshop proceedings by ibai-publishing (www.ibai-publishing.org). Selected papers of CBR-MD will be published in a special issue of the international journal Transactions on Case-Based Reasoning (www.ibai-publishing.org/journal/cbr).
Advances in Data Mining: Applications and Theoretical Aspects
Author: Petra Perner
Publisher: Springer Science & Business Media
ISBN: 3642143997
Category : Computers
Languages : en
Pages : 667
Book Description
These are the proceedings of the tenth event of the Industrial Conference on Data Mining ICDM held in Berlin (www.data-mining-forum.de). For this edition the Program Committee received 175 submissions. After the pe- review process, we accepted 49 high-quality papers for oral presentation that are included in this book. The topics range from theoretical aspects of data mining to app- cations of data mining such as on multimedia data, in marketing, finance and telec- munication, in medicine and agriculture, and in process control, industry and society. Extended versions of selected papers will appear in the international journal Trans- tions on Machine Learning and Data Mining (www.ibai-publishing.org/journal/mldm). Ten papers were selected for poster presentations and are published in the ICDM Poster Proceeding Volume by ibai-publishing (www.ibai-publishing.org). In conjunction with ICDM four workshops were held on special hot applicati- oriented topics in data mining: Data Mining in Marketing DMM, Data Mining in LifeScience DMLS, the Workshop on Case-Based Reasoning for Multimedia Data CBR-MD, and the Workshop on Data Mining in Agriculture DMA. The Workshop on Data Mining in Agriculture ran for the first time this year. All workshop papers will be published in the workshop proceedings by ibai-publishing (www.ibai-publishing.org). Selected papers of CBR-MD will be published in a special issue of the international journal Transactions on Case-Based Reasoning (www.ibai-publishing.org/journal/cbr).
Publisher: Springer Science & Business Media
ISBN: 3642143997
Category : Computers
Languages : en
Pages : 667
Book Description
These are the proceedings of the tenth event of the Industrial Conference on Data Mining ICDM held in Berlin (www.data-mining-forum.de). For this edition the Program Committee received 175 submissions. After the pe- review process, we accepted 49 high-quality papers for oral presentation that are included in this book. The topics range from theoretical aspects of data mining to app- cations of data mining such as on multimedia data, in marketing, finance and telec- munication, in medicine and agriculture, and in process control, industry and society. Extended versions of selected papers will appear in the international journal Trans- tions on Machine Learning and Data Mining (www.ibai-publishing.org/journal/mldm). Ten papers were selected for poster presentations and are published in the ICDM Poster Proceeding Volume by ibai-publishing (www.ibai-publishing.org). In conjunction with ICDM four workshops were held on special hot applicati- oriented topics in data mining: Data Mining in Marketing DMM, Data Mining in LifeScience DMLS, the Workshop on Case-Based Reasoning for Multimedia Data CBR-MD, and the Workshop on Data Mining in Agriculture DMA. The Workshop on Data Mining in Agriculture ran for the first time this year. All workshop papers will be published in the workshop proceedings by ibai-publishing (www.ibai-publishing.org). Selected papers of CBR-MD will be published in a special issue of the international journal Transactions on Case-Based Reasoning (www.ibai-publishing.org/journal/cbr).
Advances on Data Mining: Applications and Theoretical Aspects
Author: Petra Perner
Publisher: Springer Science & Business Media
ISBN: 3642231837
Category : Computers
Languages : en
Pages : 340
Book Description
This book constitutes the refereed proceedings of the 11th Industrial Conference on Data Mining, ICDM 2011, held in New York, USA in September 2011. The 22 revised full papers presented were carefully reviewed and selected from 100 submissions. The papers are organized in topical sections on data mining in medicine and agriculture, data mining in marketing, data mining for Industrial processes and in telecommunication, Multimedia Data Mining, theoretical aspects of data mining, Data Warehousing, WebMining and Information Mining.
Publisher: Springer Science & Business Media
ISBN: 3642231837
Category : Computers
Languages : en
Pages : 340
Book Description
This book constitutes the refereed proceedings of the 11th Industrial Conference on Data Mining, ICDM 2011, held in New York, USA in September 2011. The 22 revised full papers presented were carefully reviewed and selected from 100 submissions. The papers are organized in topical sections on data mining in medicine and agriculture, data mining in marketing, data mining for Industrial processes and in telecommunication, Multimedia Data Mining, theoretical aspects of data mining, Data Warehousing, WebMining and Information Mining.
Advances in Data Mining - Theoretical Aspects and Applications
Author: Petra Perner
Publisher: Springer
ISBN: 354073435X
Category : Computers
Languages : en
Pages : 362
Book Description
The papers in this volume represent the proceedings of the 7th Industrial Conference on Data Mining. They are organized into topical sections on aspects of classification and prediction, clustering, web mining, data mining in medicine, applications of data mining, time series and frequent pattern mining, and association rule mining. Readers gain new insights into theories underlying data mining and discover state-of-the-technology applications.
Publisher: Springer
ISBN: 354073435X
Category : Computers
Languages : en
Pages : 362
Book Description
The papers in this volume represent the proceedings of the 7th Industrial Conference on Data Mining. They are organized into topical sections on aspects of classification and prediction, clustering, web mining, data mining in medicine, applications of data mining, time series and frequent pattern mining, and association rule mining. Readers gain new insights into theories underlying data mining and discover state-of-the-technology applications.
Advances in Data Mining. Applications and Theoretical Aspects
Author: Petra Perner
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
Recent Advances in Data Mining of Enterprise Data
Author: T. Warren Liao
Publisher: World Scientific
ISBN: 9812779868
Category : Business & Economics
Languages : en
Pages : 816
Book Description
The main goal of the new field of data mining is the analysis of large and complex datasets. Some very important datasets may be derived from business and industrial activities. This kind of data is known as OC enterprise dataOCO. The common characteristic of such datasets is that the analyst wishes to analyze them for the purpose of designing a more cost-effective strategy for optimizing some type of performance measure, such as reducing production time, improving quality, eliminating wastes, or maximizing profit. Data in this category may describe different scheduling scenarios in a manufacturing environment, quality control of some process, fault diagnosis in the operation of a machine or process, risk analysis when issuing credit to applicants, management of supply chains in a manufacturing system, or data for business related decision-making. Sample Chapter(s). Foreword (37 KB). Chapter 1: Enterprise Data Mining: A Review and Research Directions (655 KB). Contents: Enterprise Data Mining: A Review and Research Directions (T W Liao); Application and Comparison of Classification Techniques in Controlling Credit Risk (L Yu et al.); Predictive Classification with Imbalanced Enterprise Data (S Daskalaki et al.); Data Mining Applications of Process Platform Formation for High Variety Production (J Jiao & L Zhang); Multivariate Control Charts from a Data Mining Perspective (G C Porzio & G Ragozini); Maintenance Planning Using Enterprise Data Mining (L P Khoo et al.); Mining Images of Cell-Based Assays (P Perner); Support Vector Machines and Applications (T B Trafalis & O O Oladunni); A Survey of Manifold-Based Learning Methods (X Huo et al.); and other papers. Readership: Graduate students in engineering, computer science, and business schools; researchers and practioners of data mining with emphazis of enterprise data mining."
Publisher: World Scientific
ISBN: 9812779868
Category : Business & Economics
Languages : en
Pages : 816
Book Description
The main goal of the new field of data mining is the analysis of large and complex datasets. Some very important datasets may be derived from business and industrial activities. This kind of data is known as OC enterprise dataOCO. The common characteristic of such datasets is that the analyst wishes to analyze them for the purpose of designing a more cost-effective strategy for optimizing some type of performance measure, such as reducing production time, improving quality, eliminating wastes, or maximizing profit. Data in this category may describe different scheduling scenarios in a manufacturing environment, quality control of some process, fault diagnosis in the operation of a machine or process, risk analysis when issuing credit to applicants, management of supply chains in a manufacturing system, or data for business related decision-making. Sample Chapter(s). Foreword (37 KB). Chapter 1: Enterprise Data Mining: A Review and Research Directions (655 KB). Contents: Enterprise Data Mining: A Review and Research Directions (T W Liao); Application and Comparison of Classification Techniques in Controlling Credit Risk (L Yu et al.); Predictive Classification with Imbalanced Enterprise Data (S Daskalaki et al.); Data Mining Applications of Process Platform Formation for High Variety Production (J Jiao & L Zhang); Multivariate Control Charts from a Data Mining Perspective (G C Porzio & G Ragozini); Maintenance Planning Using Enterprise Data Mining (L P Khoo et al.); Mining Images of Cell-Based Assays (P Perner); Support Vector Machines and Applications (T B Trafalis & O O Oladunni); A Survey of Manifold-Based Learning Methods (X Huo et al.); and other papers. Readership: Graduate students in engineering, computer science, and business schools; researchers and practioners of data mining with emphazis of enterprise data mining."
Advances in Data Mining. Applications and Theoretical Aspects
Author: Petra Perner
Publisher: Springer
ISBN: 3319627015
Category : Computers
Languages : en
Pages : 356
Book Description
This book constitutes the refereed proceedings of the 17th Industrial Conference on Advances in Data Mining, ICDM 2017, held in New York, NY, USA, in July 2017. The 27 revised full papers presented were carefully reviewed and selected from 71 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 in process control in industry and society.
Publisher: Springer
ISBN: 3319627015
Category : Computers
Languages : en
Pages : 356
Book Description
This book constitutes the refereed proceedings of the 17th Industrial Conference on Advances in Data Mining, ICDM 2017, held in New York, NY, USA, in July 2017. The 27 revised full papers presented were carefully reviewed and selected from 71 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 in process control in industry and society.
Ethical Data Mining Applications for Socio-Economic Development
Author: Hakikur Rahman
Publisher: IGI Global
ISBN: 1466640790
Category : Computers
Languages : en
Pages : 360
Book Description
"This book provides an overview of data mining techniques under an ethical lens, investigating developments in research best practices and examining experimental cases to identify potential ethical dilemmas in the information and communications technology sector"--Provided by publisher.
Publisher: IGI Global
ISBN: 1466640790
Category : Computers
Languages : en
Pages : 360
Book Description
"This book provides an overview of data mining techniques under an ethical lens, investigating developments in research best practices and examining experimental cases to identify potential ethical dilemmas in the information and communications technology sector"--Provided by publisher.
Advances in Data Mining
Author: Petra Perner
Publisher: Springer
ISBN: 3540360379
Category : Computers
Languages : en
Pages : 602
Book Description
This book constitutes the refereed proceedings of the 6th Industrial Conference on Data Mining, ICDM 2006, held in Leipzig, Germany in July 2006. Presents 45 carefully reviewed and revised full papers organized in topical sections on data mining in medicine, Web mining and logfile analysis, theoretical aspects of data mining, data mining in marketing, mining signals and images, and aspects of data mining, and applications such as intrusion detection, and more.
Publisher: Springer
ISBN: 3540360379
Category : Computers
Languages : en
Pages : 602
Book Description
This book constitutes the refereed proceedings of the 6th Industrial Conference on Data Mining, ICDM 2006, held in Leipzig, Germany in July 2006. Presents 45 carefully reviewed and revised full papers organized in topical sections on data mining in medicine, Web mining and logfile analysis, theoretical aspects of data mining, data mining in marketing, mining signals and images, and aspects of data mining, and applications such as intrusion detection, and more.
Temporal Data Mining
Author: Theophano Mitsa
Publisher: CRC Press
ISBN: 1420089773
Category : Business & Economics
Languages : en
Pages : 398
Book Description
From basic data mining concepts to state-of-the-art advances, this book covers the theory of the subject as well as its application in a variety of fields. It discusses the incorporation of temporality in databases as well as temporal data representation, similarity computation, data classification, clustering, pattern discovery, and prediction. The book also explores the use of temporal data mining in medicine and biomedical informatics, business and industrial applications, web usage mining, and spatiotemporal data mining. Along with various state-of-the-art algorithms, each chapter includes detailed references and short descriptions of relevant algorithms and techniques described in other references.
Publisher: CRC Press
ISBN: 1420089773
Category : Business & Economics
Languages : en
Pages : 398
Book Description
From basic data mining concepts to state-of-the-art advances, this book covers the theory of the subject as well as its application in a variety of fields. It discusses the incorporation of temporality in databases as well as temporal data representation, similarity computation, data classification, clustering, pattern discovery, and prediction. The book also explores the use of temporal data mining in medicine and biomedical informatics, business and industrial applications, web usage mining, and spatiotemporal data mining. Along with various state-of-the-art algorithms, each chapter includes detailed references and short descriptions of relevant algorithms and techniques described in other references.
Mathematical Tools for Data Mining
Author: Dan A. Simovici
Publisher: Springer Science & Business Media
ISBN: 1848002017
Category : Computers
Languages : en
Pages : 611
Book Description
This volume was born from the experience of the authors as researchers and educators,whichsuggeststhatmanystudentsofdataminingarehandicapped in their research by the lack of a formal, systematic education in its mat- matics. The data mining literature contains many excellent titles that address the needs of users with a variety of interests ranging from decision making to p- tern investigation in biological data. However, these books do not deal with the mathematical tools that are currently needed by data mining researchers and doctoral students. We felt it timely to produce a book that integrates the mathematics of data mining with its applications. We emphasize that this book is about mathematical tools for data mining and not about data mining itself; despite this, a substantial amount of applications of mathematical c- cepts in data mining are presented. The book is intended as a reference for the working data miner. In our opinion, three areas of mathematics are vital for data mining: set theory,includingpartially orderedsetsandcombinatorics;linear algebra,with its many applications in principal component analysis and neural networks; and probability theory, which plays a foundational role in statistics, machine learning and data mining. Thisvolumeisdedicatedtothestudyofset-theoreticalfoundationsofdata mining. Two further volumes are contemplated that will cover linear algebra and probability theory. The ?rst part of this book, dedicated to set theory, begins with a study of functionsandrelations.Applicationsofthesefundamentalconceptstosuch- sues as equivalences and partitions are discussed. Also, we prepare the ground for the following volumes by discussing indicator functions, ?elds and?-?elds, and other concepts.
Publisher: Springer Science & Business Media
ISBN: 1848002017
Category : Computers
Languages : en
Pages : 611
Book Description
This volume was born from the experience of the authors as researchers and educators,whichsuggeststhatmanystudentsofdataminingarehandicapped in their research by the lack of a formal, systematic education in its mat- matics. The data mining literature contains many excellent titles that address the needs of users with a variety of interests ranging from decision making to p- tern investigation in biological data. However, these books do not deal with the mathematical tools that are currently needed by data mining researchers and doctoral students. We felt it timely to produce a book that integrates the mathematics of data mining with its applications. We emphasize that this book is about mathematical tools for data mining and not about data mining itself; despite this, a substantial amount of applications of mathematical c- cepts in data mining are presented. The book is intended as a reference for the working data miner. In our opinion, three areas of mathematics are vital for data mining: set theory,includingpartially orderedsetsandcombinatorics;linear algebra,with its many applications in principal component analysis and neural networks; and probability theory, which plays a foundational role in statistics, machine learning and data mining. Thisvolumeisdedicatedtothestudyofset-theoreticalfoundationsofdata mining. Two further volumes are contemplated that will cover linear algebra and probability theory. The ?rst part of this book, dedicated to set theory, begins with a study of functionsandrelations.Applicationsofthesefundamentalconceptstosuch- sues as equivalences and partitions are discussed. Also, we prepare the ground for the following volumes by discussing indicator functions, ?elds and?-?elds, and other concepts.