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Research and Development in Knowledge Discovery and Data Mining

Research and Development in Knowledge Discovery and Data Mining PDF Author: Xindong Wu
Publisher:
ISBN: 9783662174012
Category :
Languages : en
Pages : 452

Book Description


Research and Development in Knowledge Discovery and Data Mining

Research and Development in Knowledge Discovery and Data Mining PDF Author: Xindong Wu
Publisher:
ISBN: 9783662174012
Category :
Languages : en
Pages : 452

Book Description


Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining PDF Author: Usama M. Fayyad
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 638

Book Description
Eight sections of this book span fundamental issues of knowledge discovery, classification and clustering, trend and deviation analysis, dependency derivation, integrated discovery systems, augumented database systems and application case studies. The appendices provide a list of terms used in the literature of the field of data mining and knowledge discovery in databases, and a list of online resources for the KDD researcher.

Research and Development in Knowledge Discovery and Data Mining

Research and Development in Knowledge Discovery and Data Mining PDF Author: Xindong Wu
Publisher: Springer
ISBN: 3540697683
Category : Computers
Languages : en
Pages : 440

Book Description
This book constitutes the refereed proceedings of the Second Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD-98, held in Melbourne, Australia, in April 1998. The book presents 30 revised full papers selected from a total of 110 submissions; also included are 20 poster presentations. The papers contribute new results to all current aspects in knowledge discovery and data mining on the research level as well as on the level of systems development. Among the areas covered are machine learning, information systems, the Internet, statistics, knowledge acquisition, data visualization, software reengineering, and knowledge based systems.

Rough Sets and Data Mining

Rough Sets and Data Mining PDF Author: T.Y. Lin
Publisher: Springer Science & Business Media
ISBN: 1461314615
Category : Computers
Languages : en
Pages : 429

Book Description
Rough Sets and Data Mining: Analysis of Imprecise Data is an edited collection of research chapters on the most recent developments in rough set theory and data mining. The chapters in this work cover a range of topics that focus on discovering dependencies among data, and reasoning about vague, uncertain and imprecise information. The authors of these chapters have been careful to include fundamental research with explanations as well as coverage of rough set tools that can be used for mining data bases. The contributing authors consist of some of the leading scholars in the fields of rough sets, data mining, machine learning and other areas of artificial intelligence. Among the list of contributors are Z. Pawlak, J Grzymala-Busse, K. Slowinski, and others. Rough Sets and Data Mining: Analysis of Imprecise Data will be a useful reference work for rough set researchers, data base designers and developers, and for researchers new to the areas of data mining and rough sets.

Complex Data Warehousing and Knowledge Discovery for Advanced Retrieval Development: Innovative Methods and Applications

Complex Data Warehousing and Knowledge Discovery for Advanced Retrieval Development: Innovative Methods and Applications PDF Author: Nguyen, Tho Manh
Publisher: IGI Global
ISBN: 1605667498
Category : Education
Languages : en
Pages : 426

Book Description
Recently, researchers have focused on challenging problems facing the development of data warehousing, knowledge discovery, and data mining applications.

Urban Informatics

Urban Informatics PDF Author: Wenzhong Shi
Publisher: Springer Nature
ISBN: 9811589836
Category : Social Science
Languages : en
Pages : 941

Book Description
This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity.

Research and Development in Knowledge Discovery and Data Mining

Research and Development in Knowledge Discovery and Data Mining PDF Author: Xindong Wu
Publisher: Springer
ISBN: 9783540643838
Category : Computers
Languages : en
Pages : 434

Book Description
This book constitutes the refereed proceedings of the Second Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD-98, held in Melbourne, Australia, in April 1998. The book presents 30 revised full papers selected from a total of 110 submissions; also included are 20 poster presentations. The papers contribute new results to all current aspects in knowledge discovery and data mining on the research level as well as on the level of systems development. Among the areas covered are machine learning, information systems, the Internet, statistics, knowledge acquisition, data visualization, software reengineering, and knowledge based systems.

Data Mining and Knowledge Discovery with Evolutionary Algorithms

Data Mining and Knowledge Discovery with Evolutionary Algorithms PDF Author: Alex A. Freitas
Publisher: Springer Science & Business Media
ISBN: 3662049236
Category : Computers
Languages : en
Pages : 272

Book Description
This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increasingly popular in the last few years, and their integration is currently an active research area. In general, data mining consists of extracting knowledge from data. The motivation for applying evolutionary algorithms to data mining is that evolutionary algorithms are robust search methods which perform a global search in the space of candidate solutions. This book emphasizes the importance of discovering comprehensible, interesting knowledge, which is potentially useful for intelligent decision making. The text explains both basic concepts and advanced topics

Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining PDF Author: Kyu-Young Whang
Publisher: Springer
ISBN: 3540361758
Category : Computers
Languages : en
Pages : 629

Book Description
The 7th Paci?c Asia Conference on Knowledge Discovery and Data Mining (PAKDD) was held from April 30 to May 2, 2003 in the Convention and Ex- bition Center (COEX), Seoul, Korea. The PAKDD conference is a major forum for academic researchers and industry practitioners in the Paci?c Asia region to share original research results and development experiences from di?erent KDD-related areas such as data mining, data warehousing, machine learning, databases, statistics, knowledge acquisition and discovery, data visualization, and knowledge-based systems. The conference was organized by the Advanced Information Technology Research Center (AITrc) at KAIST and the Statistical Research Center for Complex Systems (SRCCS) at Seoul National University. It was sponsored by the Korean Datamining Society (KDMS), the Korea Inf- mation Science Society (KISS), the United States Air Force O?ce of Scienti?c Research, the Asian O?ce of Aerospace Research & Development, and KAIST. It was held with cooperation from ACM’s Special Group on Knowledge Dis- very and Data Mining (SIGKDD).

Scientific Data Mining and Knowledge Discovery

Scientific Data Mining and Knowledge Discovery PDF Author: Mohamed Medhat Gaber
Publisher: Springer Science & Business Media
ISBN: 3642027881
Category : Computers
Languages : en
Pages : 398

Book Description
Mohamed Medhat Gaber “It is not my aim to surprise or shock you – but the simplest way I can summarise is to say that there are now in the world machines that think, that learn and that create. Moreover, their ability to do these things is going to increase rapidly until – in a visible future – the range of problems they can handle will be coextensive with the range to which the human mind has been applied” by Herbert A. Simon (1916-2001) 1Overview This book suits both graduate students and researchers with a focus on discovering knowledge from scienti c data. The use of computational power for data analysis and knowledge discovery in scienti c disciplines has found its roots with the re- lution of high-performance computing systems. Computational science in physics, chemistry, and biology represents the rst step towards automation of data analysis tasks. The rational behind the developmentof computationalscience in different - eas was automating mathematical operations performed in those areas. There was no attention paid to the scienti c discovery process. Automated Scienti c Disc- ery (ASD) [1–3] represents the second natural step. ASD attempted to automate the process of theory discovery supported by studies in philosophy of science and cognitive sciences. Although early research articles have shown great successes, the area has not evolved due to many reasons. The most important reason was the lack of interaction between scientists and the automating systems.