Sebanyak 291 item atau buku ditemukan

Advances in Knowledge Discovery and Data Mining

12th Pacific-Asia Conference, PAKDD 2008 Osaka, Japan, May 20-23, 2008 Proceedings

This book constitutes the refereed proceedings of the 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2008, held in Osaka, Japan, in May 2008. The 37 revised long papers, 40 revised full papers, and 36 revised short papers presented together with 1 keynote talk and 4 invited lectures were carefully reviewed and selected from 312 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas including data mining, data warehousing, machine learning, databases, statistics, knowledge acquisition, automatic scientific discovery, data visualization, causal induction, and knowledge-based systems.

As data mining having attracted a significant amount of re- search attention, many
clustering methods have been proposed in past decades. However, most of
those techniques have annoying obstacles in precise pattern recognition.

Data Mining for Business Applications

Data Mining for Business Applications presents the state-of-the-art research and development outcomes on methodologies, techniques, approaches and successful applications in the area. The contributions mark a paradigm shift from “data-centered pattern mining” to “domain driven actionable knowledge discovery” for next-generation KDD research and applications. The contents identify how KDD techniques can better contribute to critical domain problems in theory and practice, and strengthen business intelligence in complex enterprise applications. The volume also explores challenges and directions for future research and development in the dialogue between academia and business.

However, in order to efficiently run these data mining algorithms or techniques,
the human actor needs to set up the various parameters. He or she will have to
use their knowledge to make a choice of parameter values that accurately reflect
 ...

Foundations and Novel Approaches in Data Mining

Data-mining has become a popular research topic in recent years for the treatment of the "data rich and information poor" syndrome. Currently, application oriented engineers are only concerned with their immediate problems, which results in an ad hoc method of problem solving. Researchers, on the other hand, lack an understanding of the practical issues of data-mining for real-world problems and often concentrate on issues that are of no significance to the practitioners. In this volume, we hope to remedy problems by (1) presenting a theoretical foundation of data-mining, and (2) providing important new directions for data-mining research. A set of well respected data mining theoreticians were invited to present their views on the fundamental science of data mining. We have also called on researchers with practical data mining experiences to present new important data-mining topics.

Workflow. Mining. Kwang-Hoon Kim1 and Clarence A. Ellis2 1 Collaboration
Technology Research Lab. Department of Computer Science KYONGGI
UNIVERSITY San 94-6 Yiuidong Youngtongku Suwonsi Kyonggido, South Korea
, 442-760 ...

Advances in Data Mining: Applications and Theoretical Aspects

10th Industrial Conference, ICDM 2010, Berlin, Germany, July 12-14, 2010. Proceedings

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).

10th Industrial Conference, ICDM 2010, Berlin, Germany, July 12-14, 2010.
Proceedings Petra Perner. Re-mining Positive and Negative Association Mining
Results Ayhan Demiriz1, Gurdal Ertek2, Tankut Atan3, and Ufuk Kula1 1 Sakarya
 ...

Advances in Data Mining. Medical Applications, E-Commerce, Marketing, and Theoretical Aspects

8th Industrial Conference, ICDM 2008 Leipzig, Germany, July 16-18, 2008, Proceedings

ICDM / MLDM Medaillie (limited edition) Meissner Porcellan, the “White Gold” of King August the Strongest of Saxonia ICDM 2008 was the eighth event of the Industrial Conference on Data Mining held in Leipzig (www.data-mining-forum.de). For this edition the Program Committee received 116 submissions from 20 countries. After the peer-review process, we accepted 36 high-quality papers for oral presentation, which are included in these proceedings. The topics range from 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. Thirteen papers were selected for poster presentations that are published in the ICDM Poster Proceeding Volume. In conjunction with ICDM there were three workshops focusing on special hot application-oriented topics in data mining. The workshop Data Mining in Life Science DMLS 2008 was held the third time this year and the workshop Data Mining in Marketing DMM 2008 ran for the second time this year. Additionally, we introduced an International Workshop on Case-Based Reasoning for Multimedia Data CBR-MD.

Data Mining with Neural Networks for Wheat Yield Prediction Georg Ruß1,
Rudolf Kruse1, Martin Schneider2, and Peter Wagner2 1 Otto-von-Guericke-
University of Magdeburg 2 Martin-Luther-University of Halle Abstract. Precision
agriculture ...

Advances in Knowledge Discovery and Data Mining

11th Pacific-Asia Conference, PAKDD 2007, Nanjing, China, May 22-25, 2007, Proceedings

This book constitutes the refereed proceedings of the 11th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2007, held in Nanjing, China in May 2007.The 34 revised full papers and 92 revised short papers presented together with 4 keynote talks or extended abstracts thereof were carefully reviewed and selected from 730 submissions. The papers are devoted to new ideas, original research results and practical development experiences from all KDD-related areas including data mining, machine learning, databases, statistics, data warehousing, data visualization, automatic scientific discovery, knowledge acquisition and knowledge-based systems.

Mining. Through. Amalgamating. Temporal. Workcases. Kwanghoon Kim1 and
Clarence A. Ellis2 1 Collaboration Technology Research Lab Department of
Computer Science KYONGGI UNIVERSITY San 94-6 Yiui-dong Youngtong-ku ...

Pocket Data Mining

Big Data on Small Devices

Owing to continuous advances in the computational power of handheld devices like smartphones and tablet computers, it has become possible to perform Big Data operations including modern data mining processes onboard these small devices. A decade of research has proved the feasibility of what has been termed as Mobile Data Mining, with a focus on one mobile device running data mining processes. However, it is not before 2010 until the authors of this book initiated the Pocket Data Mining (PDM) project exploiting the seamless communication among handheld devices performing data analysis tasks that were infeasible until recently. PDM is the process of collaboratively extracting knowledge from distributed data streams in a mobile computing environment. This book provides the reader with an in-depth treatment on this emerging area of research. Details of techniques used and thorough experimental studies are given. More importantly and exclusive to this book, the authors provide detailed practical guide on the deployment of PDM in the mobile environment. An important extension to the basic implementation of PDM dealing with concept drift is also reported. In the era of Big Data, potential applications of paramount importance offered by PDM in a variety of domains including security, business and telemedicine are discussed.

Mobile data mining, data stream mining, and parallel and distributed data mining
and mobile software agents are four areas that collectively contributed to the
possibility of developing PDM. Mobile software agents as a flexible software ...

Perception-based Data Mining and Decision Making in Economics and Finance

The primary goal of this book is to present to the scientific and management communities a selection of applications using recent Soft Computing (SC) and Computing with Words and Perceptions (CWP) models and techniques meant to solve some economics and financial problems that are of utmost importance. The book starts with a coverage of data mining tools and techniques that may be of use and significance for economic and financial analyses and applications. Notably, fuzzy and natural language based approaches and solutions for a more human consistent dealing with decision support, time series analysis, forecasting, clustering, etc. are discussed. The second part deals with various decision making models, particularly under probabilistic and fuzzy uncertainty, and their applications in solving a wide array of problems including portfolio optimization, option pricing, financial engineering, risk analysis etc. The selected examples could also serve as a starting point or as an opening out, in the SC and CWP techniques application to a wider range of problems in economics and finance.

Mining. I. Batyrshin, L. Sheremetov, and R. Herrera-Avelar Summary. Import of
intelligent features to systems supporting human decisions in problems related
with analysis of time series data bases is a promising research field. Such
systems ...

Mobility, Data Mining and Privacy

Geographic Knowledge Discovery

Mobile communications and ubiquitous computing generate large volumes of data. Mining this data can produce useful knowledge, yet individual privacy is at risk. This book investigates the various scientific and technological issues of mobility data, open problems, and roadmap. The editors manage a research project called GeoPKDD, Geographic Privacy-Aware Knowledge Discovery and Delivery, and this book relates their findings in 13 chapters covering all related subjects.

In the area of data mining, we have seen a similar development. Many data
mining techniques – such as frequent set and association rule mining,
classification, prediction and clustering – were first developed for typical alpha-
numerical ...

Data Mining: Foundations and Practice

This book contains valuable studies in data mining from both foundational and practical perspectives. The foundational studies of data mining may help to lay a solid foundation for data mining as a scientific discipline, while the practical studies of data mining may lead to new data mining paradigms and algorithms. The foundational studies contained in this book focus on a broad range of subjects, including conceptual framework of data mining, data preprocessing and data mining as generalization, probability theory perspective on fuzzy systems, rough set methodology on missing values, inexact multiple-grained causal complexes, complexity of the privacy problem, logical framework for template creation and information extraction, classes of association rules, pseudo statistical independence in a contingency table, and role of sample size and determinants in granularity of contingency matrix. The practical studies contained in this book cover different fields of data mining, including rule mining, classification, clustering, text mining, Web mining, data stream mining, time series analysis, privacy preservation mining, fuzzy data mining, ensemble approaches, and kernel based approaches. We believe that the works presented in this book will encourage the study of data mining as a scientific field and spark collaboration among researchers and practitioners.

Does Relevance Matter to Data Mining Research? Mykola Pechenizkiy1,2,
Seppo Puuronen2, and Alexey Tsymbal3,4 1 Information Systems Group,
Department of Computer Science, Eindhoven University of Technology, P.O. Box
513, 5600 ...