Geographic Data Mining and Knowledge Discovery

Geographic Data Mining and Knowledge Discovery PDF

Author: Harvey J. Miller

Publisher: CRC Press

Published: 2009-05-27

Total Pages: 486

ISBN-13: 1420073982

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The Definitive Volume on Cutting-Edge Exploratory Analysis of Massive Spatial and Spatiotemporal DatabasesSince the publication of the first edition of Geographic Data Mining and Knowledge Discovery, new techniques for geographic data warehousing (GDW), spatial data mining, and geovisualization (GVis) have been developed. In addition, there has bee

Mobility, Data Mining and Privacy

Mobility, Data Mining and Privacy PDF

Author: Fosca Giannotti

Publisher: Springer Science & Business Media

Published: 2008-01-12

Total Pages: 415

ISBN-13: 3540751777

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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.

Spatial Data Mining

Spatial Data Mining PDF

Author: Deren Li

Publisher: Springer

Published: 2016-03-23

Total Pages: 308

ISBN-13: 3662485389

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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’.

Geographic Data Mining and Knowledge Discovery

Geographic Data Mining and Knowledge Discovery PDF

Author: Harvey J. Miller

Publisher:

Published: 2001

Total Pages: 372

ISBN-13: 9780203245804

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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. Data Mining 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.

Knowledge Discovery in Spatial Data

Knowledge Discovery in Spatial Data PDF

Author: Yee Leung

Publisher: Springer Science & Business Media

Published: 2010-03-14

Total Pages: 381

ISBN-13: 3642026648

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When I ?rst came across the term data mining and knowledge discovery in databases, I was excited and curious to ?nd out what it was all about. I was excited because the term tends to convey a new ?eld that is in the making. I was curious because I wondered what it was doing that the other ?elds of research, such as statistics and the broad ?eld of arti?cial intelligence, were not doing. After reading up on the literature, I have come to realize that it is not much different from conventional data analysis. The commonly used de?nition of knowledge discovery in databases: “the non-trivial process of identifying valid, novel, potentially useful, and ultimately understandable patterns in data” is actually in line with the core mission of conventional data analysis. The process employed by conventional data analysis is by no means trivial, and the patterns in data to be unraveled have, of course, to be valid, novel, useful and understandable. Therefore, what is the commotion all about? Careful scrutiny of the main lines of research in data mining and knowledge discovery again told me that they are not much different from that of conventional data analysis. Putting aside data warehousing and database m- agement aspects, again a main area of research in conventional database research, the rest of the tasks in data mining are largely the main concerns of conventional data analysis.

Advances in Spatial Databases

Advances in Spatial Databases PDF

Author: Michel Scholl

Publisher: Springer Science & Business Media

Published: 1997-07-02

Total Pages: 404

ISBN-13: 9783540632382

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Content Description #Includes bibliographical references and index.

KI-99: Advances in Artificial Intelligence

KI-99: Advances in Artificial Intelligence PDF

Author: Wolfram Burgard

Publisher: Springer Science & Business Media

Published: 1999-09-01

Total Pages: 321

ISBN-13: 3540664955

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For many years, Arti?cial Intelligence technology has served in a great variety of successful applications. AI researchand researchershave contributed much to the vision of the so-called Information Society. As early as the 1980s, some of us imagined distributed knowledge bases containing the explicable knowledge of a company or any other organization. Today, such systems are becoming reality. In the process, other technologies have had to be developed and AI-technology has blended with them, and companies are now sensitive to this topic. TheInternetandWWWhaveprovidedtheglobalinfrastructure,whileatthe same time companies have become global in nearly every aspect of enterprise. This process has just started, a little experience has been gained, and therefore it is tempting to re?ect and try to forecast, what the next steps may be. This has given us one of the two main topics of the 23rd Annual German Conference on Arti?cial Intelligence (KI-99)held at the University of Bonn: The Knowledge Society. Two of our invited speakers, Helmut Willke, Bielefeld, and Hans-Peter Kriegel, Munich, dwell on di?erent aspects with di?erent perspectives. Helmut Willke deals with the concept of virtual organizations, while Hans-Peter Kriegel applies data mining concepts to pattern recognitiontasks.The three application forums are also part of the Knowledge Society topic: “IT-based innovation for environment and development”, “Knowledge management in enterprises”, and “Knowledgemanagementinvillageandcityplanningoftheinformationsociety”.

Information Visualization in Data Mining and Knowledge Discovery

Information Visualization in Data Mining and Knowledge Discovery PDF

Author: Usama M. Fayyad

Publisher: Morgan Kaufmann

Published: 2002

Total Pages: 446

ISBN-13: 9781558606890

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This text surveys research from the fields of data mining and information visualisation and presents a case for techniques by which information visualisation can be used to uncover real knowledge hidden away in large databases.

Urban Informatics

Urban Informatics PDF

Author: Wenzhong Shi

Publisher: Springer Nature

Published: 2021-04-06

Total Pages: 941

ISBN-13: 9811589836

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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.

Data Mining for Geoinformatics

Data Mining for Geoinformatics PDF

Author: Guido Cervone

Publisher: Springer Science & Business Media

Published: 2013-08-16

Total Pages: 175

ISBN-13: 1461476690

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The rate at which geospatial data is being generated exceeds our computational capabilities to extract patterns for the understanding of a dynamically changing world. Geoinformatics and data mining focuses on the development and implementation of computational algorithms to solve these problems. This unique volume contains a collection of chapters on state-of-the-art data mining techniques applied to geoinformatic problems of high complexity and important societal value. Data Mining for Geoinformatics addresses current concerns and developments relating to spatio-temporal data mining issues in remotely-sensed data, problems in meteorological data such as tornado formation, estimation of radiation from the Fukushima nuclear power plant, simulations of traffic data using OpenStreetMap, real time traffic applications of data stream mining, visual analytics of traffic and weather data and the exploratory visualization of collective, mobile objects such as the flocking behavior of wild chickens. This book is designed for researchers and advanced-level students focused on computer science, earth science and geography as a reference or secondary text book. Practitioners working in the areas of data mining and geoscience will also find this book to be a valuable reference.

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