Data Mining Southeast Asia Edition

Author: Jiawei Han
Publisher: Elsevier
ISBN: 9780080475585
Format: PDF, Docs
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Our ability to generate and collect data has been increasing rapidly. Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication tools, and bar codes also generate data. On the collection side, scanned text and image platforms, satellite remote sensing systems, and the World Wide Web have flooded us with a tremendous amount of data. This explosive growth has generated an even more urgent need for new techniques and automated tools that can help us transform this data into useful information and knowledge. Like the first edition, voted the most popular data mining book by KD Nuggets readers, this book explores concepts and techniques for the discovery of patterns hidden in large data sets, focusing on issues relating to their feasibility, usefulness, effectiveness, and scalability. However, since the publication of the first edition, great progress has been made in the development of new data mining methods, systems, and applications. This new edition substantially enhances the first edition, and new chapters have been added to address recent developments on mining complex types of data— including stream data, sequence data, graph structured data, social network data, and multi-relational data. A comprehensive, practical look at the concepts and techniques you need to know to get the most out of real business data Updates that incorporate input from readers, changes in the field, and more material on statistics and machine learning Dozens of algorithms and implementation examples, all in easily understood pseudo-code and suitable for use in real-world, large-scale data mining projects Complete classroom support for instructors at www.mkp.com/datamining2e companion site

Spatial Database Systems

Author: Albert K.W. Yeung
Publisher: Springer Science & Business Media
ISBN: 9781402053924
Format: PDF
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This book places spatial data within the broader domain of information technology (IT) while providing a comprehensive and coherent explanation of the guiding principles, methods, implementation and operational management of spatial databases within the workplace. The text explains the key concepts, issues and processes of spatial data implementation and provides a holistic management perspective.

Quality Aspects in Spatial Data Mining

Author: Alfred Stein
Publisher: CRC Press
ISBN: 1420069276
Format: PDF, Mobi
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Describes the State-of-the-Art in Spatial Data Mining, Focuses on Data Quality Substantial progress has been made toward developing effective techniques for spatial information processing in recent years. This science deals with models of reality in a GIS, however, and not with reality itself. Therefore, spatial information processes are often imprecise, allowing for much interpretation of abstract figures and data. Quality Aspects in Spatial Data Mining introduces practical and theoretical solutions for making sense of the often chaotic and overwhelming amount of concrete data available to researchers. In this cohesive collection of peer-reviewed chapters, field authorities present the latest field advancements and cover such essential areas as data acquisition, geoinformation theory, spatial statistics, and dissemination. Each chapter debuts with an editorial preview of each topic from a conceptual, applied, and methodological point of view, making it easier for researchers to judge which information is most beneficial to their work. Chapters Evolve From Error Propagation and Spatial Statistics to Address Relevant Applications The book advises the use of granular computing as a means of circumventing spatial complexities. This counter-application to traditional computing allows for the calculation of imprecise probabilities – the kind of information that the spatial information systems community wrestles with much of the time. Under the editorial guidance of internationally respected geoinformatics experts, this indispensable volume addresses quality aspects in the entire spatial data mining process, from data acquisition to end user. It also alleviates what is often field researchers’ most daunting task by organizing the wealth of concrete spatial data available into one convenient source, thereby advancing the frontiers of spatial information systems.

Spatial Data Mining

Author: Deren Li
Publisher: Springer
ISBN: 3662485389
Format: PDF, ePub, Mobi
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· This book is an updated version of a well-received book previously published in Chinese by Science Press of China (the first edition in 2006 and the second in 2013). It offers a systematic and practical overview of spatial data mining, which combines computer science and geo-spatial information science, allowing each field to profit from the knowledge and techniques of the other. To address the spatiotemporal specialties of spatial data, the authors introduce the key concepts and algorithms of the data field, cloud model, mining view, and Deren Li methods. The data field method captures the interactions between spatial objects by diffusing the data contribution from a universe of samples to a universe of population, thereby bridging the gap between the data model and the recognition model. The cloud model is a qualitative method that utilizes quantitative numerical characters to bridge the gap between pure data and linguistic concepts. The mining view method discriminates the different requirements by using scale, hierarchy, and granularity in order to uncover the anisotropy of spatial data mining. The Deren Li method performs data preprocessing to prepare it for further knowledge discovery by selecting a weight for iteration in order to clean the observed spatial data as much as possible. In addition to the essential algorithms and techniques, the book provides application examples of spatial data mining in geographic information science and remote sensing. The practical projects include spatiotemporal video data mining for protecting public security, serial image mining on nighttime lights for assessing the severity of the Syrian Crisis, and the applications in the government project ‘the Belt and Road Initiatives’.

Data Mining and Knowledge Discovery Handbook

Author: Oded Maimon
Publisher: Springer Science & Business Media
ISBN: 0387098232
Format: PDF, Mobi
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This book organizes key concepts, theories, standards, methodologies, trends, challenges and applications of data mining and knowledge discovery in databases. It first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. It also gives in-depth descriptions of data mining applications in various interdisciplinary industries.

Geographic Data Mining and Knowledge Discovery

Author: Harvey J. Miller
Publisher: CRC Press
ISBN: 0203468023
Format: PDF, ePub, Docs
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Advances in automated data collection are creating massive databases and a whole new field, Knowledge Discovery Databases (KDD), has emerged to develop new methods of managing and exploiting them. Geographic Data Mining and Knowledge Discovery is the interrogation of large databases using efficient computational methods. The unique challenges brought about by the storing of massive geographical databases - from high resolution satellite-based systems to data from intelligent transportation systems, for example - has led to the field of Geographical Knowledge Discovery (GKD). Geographic or spatial data mining is the exploration of these geographical information databases. Developed out of contributions to the highly-respected Varenius Project in 1999, this collection will be the definitive volume focusing on GKD and addresses the special challenges to be found in knowledge discovery and data mining from geographic databases.

Database Support for Data Mining Applications

Author: Rosa Meo
Publisher: Springer Science & Business Media
ISBN: 9783540224792
Format: PDF, Kindle
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Data mining from traditional relational databases as well as from non-traditional ones such as semi-structured data, Web data, and scientific databases housing biological, linguistic, and sensor data has recently become a popular way of discovering hidden knowledge. This book on database support for data mining is developed to approaches exploiting the available database technology, declarative data mining, intelligent querying, and associated issues, such as optimization, indexing, query processing, languages, and constraints. Attention is also paid to the solution of data preprocessing problems, such as data cleaning, discretization, and sampling. The 16 reviewed full papers presented were carefully selected from various workshops and conferences to provide complete and competent coverage of the core issues. Some papers were developed within an EC funded project on discovering knowledge with inductive queries.

Advances in Spatial Data Handling

Author: Dianne Richardson
Publisher: Springer Science & Business Media
ISBN: 3642560946
Format: PDF, ePub, Docs
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This book, entitled Advances in Spatial Data Handling, is a compendium of papers resulting from the International Symposium on Spatial Data Handling (SDH), held in Ottawa, Canada, July 9-12, 2002. The SDH conference series has been organised as one of the main activities of the International Geographical Union (IGU) since it was first started in Zurich in 1984. In the late 1990’s the IGU Commission of Geographic Information Systems was discontinued and a study group was formed to succeed it in 1997. Much like the IGU Commission, the objectives of the Study Group are to create a network of people and research centres addressing geographical information science and to facilitate exchange of information. The International Symposium on Spatial Data Handling, which is the most important activity of the IGU Study Group, has, throughout its 18 year history been highly regarded as one of the most important GIS conferences in the world.