Temporal Data Mining

Author : Theophano Mitsa
Publisher : CRC Press
ISBN 13 : 1420089773
Total Pages : 398 pages
Book Rating : 4.76/5 ( download)

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Download or read book Temporal Data Mining written by Theophano Mitsa and published by CRC Press. This book was released on 2010-03-10 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Hsu, Wynne
Publisher : IGI Global
ISBN 13 : 1599043890
Total Pages : 292 pages
Book Rating : 4.90/5 ( download)

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Download or read book Temporal and Spatio-Temporal Data Mining written by Hsu, Wynne and published by IGI Global. This book was released on 2007-07-31 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book presents probable solutions when discovering the spatial sequence patterns by incorporating the information into the sequence of patterns, and introduces new classes of spatial sequence patterns, called flow and generalized spatio-temporal patterns, addressing different scenarios in spatio-temporal data by modeling them as graphs, providing a comprehensive synopsis on two successful partition-based algorithms designed by the authors"--Provided by publisher.

Author : Yun Yang
Publisher : Elsevier
ISBN 13 : 9780128116548
Total Pages : 0 pages
Book Rating : 4.44/5 ( download)

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Download or read book Temporal Data Mining via Unsupervised Ensemble Learning written by Yun Yang and published by Elsevier. This book was released on 2016-11-21 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Temporal Data Mining via Unsupervised Ensemble Learning provides the principle knowledge of temporal data mining in association with unsupervised ensemble learning and the fundamental problems of temporal data clustering from different perspectives. By providing three proposed ensemble approaches of temporal data clustering, this book presents a practical focus of fundamental knowledge and techniques, along with a rich blend of theory and practice. Furthermore, the book includes illustrations of the proposed approaches based on data and simulation experiments to demonstrate all methodologies, and is a guide to the proper usage of these methods. As there is nothing universal that can solve all problems, it is important to understand the characteristics of both clustering algorithms and the target temporal data so the correct approach can be selected for a given clustering problem. Scientists, researchers, and data analysts working with machine learning and data mining will benefit from this innovative book, as will undergraduate and graduate students following courses in computer science, engineering, and statistics.

Author : Claudio Bettini
Publisher : Springer Science & Business Media
ISBN 13 : 3662042282
Total Pages : 232 pages
Book Rating : 4.81/5 ( download)

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Download or read book Time Granularities in Databases, Data Mining, and Temporal Reasoning written by Claudio Bettini and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Calendar and time units and specialized units, such as business days and academic years, play a major role in a wide range of information system applications. System support for reasoning about these units, called granularities, is important for the efficient design, use, and implementation of such applications. This book deals with several aspects of temporal information and provides a unifying model for granularities. Practitioners can learn about critical aspects that must be taken into account when designing and implementing databases supporting temporal information.

Author : John F. Roddick
Publisher :
ISBN 13 : 9783662180976
Total Pages : 180 pages
Book Rating : 4.79/5 ( download)

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Download or read book Temporal, Spatial, and Spatio-Temporal Data Mining written by John F. Roddick and published by . This book was released on 2014-01-15 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : Yun Yang
Publisher : Elsevier
ISBN 13 : 0128118415
Total Pages : 172 pages
Book Rating : 4.12/5 ( download)

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Download or read book Temporal Data Mining via Unsupervised Ensemble Learning written by Yun Yang and published by Elsevier. This book was released on 2016-11-15 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: Temporal Data Mining via Unsupervised Ensemble Learning provides the principle knowledge of temporal data mining in association with unsupervised ensemble learning and the fundamental problems of temporal data clustering from different perspectives. By providing three proposed ensemble approaches of temporal data clustering, this book presents a practical focus of fundamental knowledge and techniques, along with a rich blend of theory and practice. Furthermore, the book includes illustrations of the proposed approaches based on data and simulation experiments to demonstrate all methodologies, and is a guide to the proper usage of these methods. As there is nothing universal that can solve all problems, it is important to understand the characteristics of both clustering algorithms and the target temporal data so the correct approach can be selected for a given clustering problem. Scientists, researchers, and data analysts working with machine learning and data mining will benefit from this innovative book, as will undergraduate and graduate students following courses in computer science, engineering, and statistics. Includes fundamental concepts and knowledge, covering all key tasks and techniques of temporal data mining, i.e., temporal data representations, similarity measure, and mining tasks Concentrates on temporal data clustering tasks from different perspectives, including major algorithms from clustering algorithms and ensemble learning approaches Presents a rich blend of theory and practice, addressing seminal research ideas and looking at the technology from a practical point-of-view

Author : John F. Roddick
Publisher : Springer
ISBN 13 : 3540452443
Total Pages : 184 pages
Book Rating : 4.47/5 ( download)

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Download or read book Temporal, Spatial, and Spatio-Temporal Data Mining written by John F. Roddick and published by Springer. This book was released on 2003-06-29 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : National Research Council
Publisher : National Academies Press
ISBN 13 : 0309287812
Total Pages : 191 pages
Book Rating : 4.14/5 ( download)

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Download or read book Frontiers in Massive Data Analysis written by National Research Council and published by National Academies Press. This book was released on 2013-09-03 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.

Author : Natalia Andrienko
Publisher : Springer Science & Business Media
ISBN 13 : 3540311904
Total Pages : 712 pages
Book Rating : 4.04/5 ( download)

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Download or read book Exploratory Analysis of Spatial and Temporal Data written by Natalia Andrienko and published by Springer Science & Business Media. This book was released on 2006-03-28 with total page 712 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exploratory data analysis (EDA) is about detecting and describing patterns, trends, and relations in data, motivated by certain purposes of investigation. As something relevant is detected in data, new questions arise, causing specific parts to be viewed in more detail. So EDA has a significant appeal: it involves hypothesis generation rather than mere hypothesis testing. The authors describe in detail and systemize approaches, techniques, and methods for exploring spatial and temporal data in particular. They start by developing a general view of data structures and characteristics and then build on top of this a general task typology, distinguishing between elementary and synoptic tasks. This typology is then applied to the description of existing approaches and technologies, resulting not just in recommendations for choosing methods but in a set of generic procedures for data exploration. Professionals practicing analysis will profit from tested solutions – illustrated in many examples – for reuse in the catalogue of techniques presented. Students and researchers will appreciate the detailed description and classification of exploration techniques, which are not limited to spatial data only. In addition, the general principles and approaches described will be useful for designers of new methods for EDA.

Author : Vincent Lemaire
Publisher : Springer Nature
ISBN 13 : 3030914453
Total Pages : 202 pages
Book Rating : 4.55/5 ( download)

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Download or read book Advanced Analytics and Learning on Temporal Data written by Vincent Lemaire and published by Springer Nature. This book was released on 2021-12-02 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2021, held during September 13-17, 2021. The workshop was planned to take place in Bilbao, Spain, but was held virtually due to the COVID-19 pandemic. The 12 full papers presented in this book were carefully reviewed and selected from 21 submissions. They focus on the following topics: Temporal Data Clustering; Classification of Univariate and Multivariate Time Series; Multivariate Time Series Co-clustering; Efficient Event Detection; Modeling Temporal Dependencies; Advanced Forecasting and Prediction Models; Cluster-based Forecasting; Explanation Methods for Time Series Classification; Multimodal Meta-Learning for Time Series Regression; and Multivariate Time Series Anomaly Detection.