Machine Learning Algorithms for Spatio-temporal Data Mining
| Author | : Ranga Raju Vatsavai |
| Publisher | : |
| Total Pages | : 304 |
| Release | : 2008 |
| Genre | : |
| ISBN | : |
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Machine Learning Algorithms For Spatio Temporal Data Mining
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Temporal, Spatial, and Spatio-Temporal Data Mining
| Author | : John F. Roddick |
| Publisher | : Springer |
| Total Pages | : 184 |
| Release | : 2003-06-29 |
| Genre | : Computers |
| ISBN | : 3540452443 |
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This volume contains updated versions of the ten papers presented at the First International Workshop on Temporal, Spatial and Spatio-Temporal Data Mining (TSDM 2000) held in conjunction with the 4th European Conference on Prin- ples and Practice of Knowledge Discovery in Databases (PKDD 2000) in Lyons, France in September, 2000. The aim of the workshop was to bring together experts in the analysis of temporal and spatial data mining and knowledge discovery in temporal, spatial or spatio-temporal database systems as well as knowledge engineers and domain experts from allied disciplines. The workshop focused on research and practice of knowledge discovery from datasets containing explicit or implicit temporal, spatial or spatio-temporal information. The ten original papers in this volume represent those accepted by peer review following an international call for papers. All papers submitted were refereed by an international team of data mining researchers listed below. We would like to thank the team for their expert and useful help with this process. Following the workshop, authors were invited to amend their papers to enable the feedback received from the conference to be included in the ?nal papers appearing in this volume. A workshop report was compiled by Kathleen Hornsby which also discusses the panel session that was held.
Spatiotemporal Data Analytics and Modeling
| Author | : John A |
| Publisher | : Springer Nature |
| Total Pages | : 253 |
| Release | : |
| Genre | : |
| ISBN | : 9819996511 |
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Temporal Data Mining
| Author | : Theophano Mitsa |
| Publisher | : CRC Press |
| Total Pages | : 398 |
| Release | : 2010-03-10 |
| Genre | : Business & Economics |
| ISBN | : 1420089773 |
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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.
Spatiotemporal Data Analysis
| Author | : Gidon Eshel |
| Publisher | : Princeton University Press |
| Total Pages | : 337 |
| Release | : 2012 |
| Genre | : Mathematics |
| ISBN | : 069112891X |
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How do we study the storm's mutation into a deadly twister? Avian flu cases are reported in China.
An Introduction to R for Spatial Analysis and Mapping
| Author | : Chris Brunsdon |
| Publisher | : SAGE |
| Total Pages | : 386 |
| Release | : 2014-04-30 |
| Genre | : Social Science |
| ISBN | : 1473911192 |
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"In an age of big data, data journalism and with a wealth of quantitative information around us, it is not enough for students to be taught only 100 year old statistical methods using ′out of the box′ software. They need to have 21st-century analytical skills too. This is an excellent and student-friendly text from two of the world leaders in the teaching and development of spatial analysis. It shows clearly why the open source software R is not just an alternative to commercial GIS, it may actually be the better choice for mapping, analysis and for replicable research. Providing practical tips as well as fully working code, this is a practical ′how to′ guide ideal for undergraduates as well as those using R for the first time. It will be required reading on my own courses." - Richard Harris, Professor of Quantitative Social Science, University of Bristol R is a powerful open source computing tool that supports geographical analysis and mapping for the many geography and ‘non-geography’ students and researchers interested in spatial analysis and mapping. This book provides an introduction to the use of R for spatial statistical analysis, geocomputation and the analysis of geographical information for researchers collecting and using data with location attached, largely through increased GPS functionality. Brunsdon and Comber take readers from ‘zero to hero’ in spatial analysis and mapping through functions they have developed and compiled into R packages. This enables practical R applications in GIS, spatial analyses, spatial statistics, mapping, and web-scraping. Each chapter includes: Example data and commands for exploring it Scripts and coding to exemplify specific functionality Advice for developing greater understanding - through functions such as locator(), View(), and alternative coding to achieve the same ends Self-contained exercises for students to work through Embedded code within the descriptive text. This is a definitive ′how to′ that takes students - of any discipline - from coding to actual applications and uses of R.
Spatio-Temporal Data Streams
| Author | : Zdravko Galić |
| Publisher | : Springer |
| Total Pages | : 116 |
| Release | : 2016-08-26 |
| Genre | : Computers |
| ISBN | : 1493965751 |
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This SpringerBrief presents the fundamental concepts of a specialized class of data stream, spatio-temporal data streams, and demonstrates their distributed processing using Big Data frameworks and platforms. It explores a consistent framework which facilitates a thorough understanding of all different facets of the technology, from basic definitions to state-of-the-art techniques. Key topics include spatio-temporal continuous queries, distributed stream processing, SQL-like language embedding, and trajectory stream clustering. Over the course of the book, the reader will become familiar with spatio-temporal data streams management and data flow processing, which enables the analysis of huge volumes of location-aware continuous data streams. Applications range from mobile object tracking and real-time intelligent transportation systems to traffic monitoring and complex event processing. Spatio-Temporal Data Streams is a valuable resource for researchers studying spatio-temporal data streams and Big Data analytics, as well as data engineers and data scientists solving data management and analytics problems associated with this class of data.
Advanced Analytics and Learning on Temporal Data
| Author | : Vincent Lemaire |
| Publisher | : Springer Nature |
| Total Pages | : 240 |
| Release | : 2020-12-15 |
| Genre | : Computers |
| ISBN | : 3030657426 |
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This book constitutes the refereed proceedings of the 4th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2019, held in Ghent, Belgium, in September 2020. The 15 full papers presented in this book were carefully reviewed and selected from 29 submissions. The selected papers are devoted to topics such as Temporal Data Clustering; Classification of Univariate and Multivariate Time Series; Early Classification of Temporal Data; Deep Learning and Learning Representations for Temporal Data; Modeling Temporal Dependencies; Advanced Forecasting and Prediction Models; Space-Temporal Statistical Analysis; Functional Data Analysis Methods; Temporal Data Streams; Interpretable Time-Series Analysis Methods; Dimensionality Reduction, Sparsity, Algorithmic Complexity and Big Data Challenge; and Bio-Informatics, Medical, Energy Consumption, Temporal Data.
Spatial Data Mining
| Author | : Deren Li |
| Publisher | : Springer |
| Total Pages | : 329 |
| Release | : 2016-03-23 |
| Genre | : Computers |
| ISBN | : 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’.
A Historical Geography of Ghana
| Author | : Kwamina B. Dickson |
| Publisher | : CUP Archive |
| Total Pages | : 406 |
| Release | : 1969 |
| Genre | : Business & Economics |
| ISBN | : 9780521071024 |
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Originally published in 1969, this book presents a historical geography of Ghana from the earliest times onwards. It describes the people and their social organization, migrations, agriculture, artefacts, manufacturing and history. Numerous illustrative figures, appendices and a detailed bibliography are also provided. This book will be of value to anyone with an interest in Ghana and the development of historical geography.
