Data Mining in Time Series Databases

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Publisher : World Scientific
ISBN 13 : 9812382909
Total Pages : 205 pages
Book Rating : 4.8/5 (123 download)

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Book Synopsis Data Mining in Time Series Databases by : Mark Last

Download or read book Data Mining in Time Series Databases written by Mark Last and published by World Scientific. This book was released on 2004 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adding the time dimension to real-world databases produces Time Series Databases (TSDB) and introduces new aspects and difficulties to data mining and knowledge discovery. This book covers the state-of-the-art methodology for mining time series databases. The novel data mining methods presented in the book include techniques for efficient segmentation, indexing, and classification of noisy and dynamic time series. A graph-based method for anomaly detection in time series is described and the book also studies the implications of a novel and potentially useful representation of time series as strings. The problem of detecting changes in data mining models that are induced from temporal databases is additionally discussed. Contents: A Survey of Recent Methods for Efficient Retrieval of Similar Time Sequences (H M Lie); Indexing of Compressed Time Series (E Fink & K Pratt); Boosting Interval-Based Literal: Variable Length and Early Classification (J J Rodriguez Diez); Segmenting Time Series: A Survey and Novel Approach (E Keogh et al.); Indexing Similar Time Series under Conditions of Noise (M Vlachos et al.); Classification of Events in Time Series of Graphs (H Bunke & M Kraetzl); Median Strings--A Review (X Jiang et al.); Change Detection in Classfication Models of Data Mining (G Zeira et al.). Readership: Graduate students, reseachers and practitioners in the fields of data mining, machine learning, databases and statistics.

Data Mining in Time Series Databases

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Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (288 download)

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Book Synopsis Data Mining in Time Series Databases by :

Download or read book Data Mining in Time Series Databases written by and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Data Mining In Time Series And Streaming Databases

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Author :
Publisher : World Scientific
ISBN 13 : 9813228059
Total Pages : 196 pages
Book Rating : 4.8/5 (132 download)

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Book Synopsis Data Mining In Time Series And Streaming Databases by : Mark Last

Download or read book Data Mining In Time Series And Streaming Databases written by Mark Last and published by World Scientific. This book was released on 2018-01-12 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: This compendium is a completely revised version of an earlier book, Data Mining in Time Series Databases, by the same editors. It provides a unique collection of new articles written by leading experts that account for the latest developments in the field of time series and data stream mining.The emerging topics covered by the book include weightless neural modeling for mining data streams, using ensemble classifiers for imbalanced and evolving data streams, document stream mining with active learning, and many more. In particular, it addresses the domain of streaming data, which has recently become one of the emerging topics in Data Science, Big Data, and related areas. Existing titles do not provide sufficient information on this topic.

Data Mining In Time Series Databases

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Author :
Publisher : World Scientific
ISBN 13 : 981448654X
Total Pages : 205 pages
Book Rating : 4.8/5 (144 download)

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Book Synopsis Data Mining In Time Series Databases by : Horst Bunke

Download or read book Data Mining In Time Series Databases written by Horst Bunke and published by World Scientific. This book was released on 2004-06-25 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adding the time dimension to real-world databases produces Time Series Databases (TSDB) and introduces new aspects and difficulties to data mining and knowledge discovery. This book covers the state-of-the-art methodology for mining time series databases. The novel data mining methods presented in the book include techniques for efficient segmentation, indexing, and classification of noisy and dynamic time series. A graph-based method for anomaly detection in time series is described and the book also studies the implications of a novel and potentially useful representation of time series as strings. The problem of detecting changes in data mining models that are induced from temporal databases is additionally discussed.

Time Series Databases

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Publisher : O'Reilly Media
ISBN 13 : 9781491914724
Total Pages : 0 pages
Book Rating : 4.9/5 (147 download)

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Book Synopsis Time Series Databases by : Ted Dunning

Download or read book Time Series Databases written by Ted Dunning and published by O'Reilly Media. This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time series data is of growing importance, especially with the rapid expansion of the Internet of Things. This concise guide shows you effective ways to collect, persist, and access large-scale time series data for analysis. You'll explore the theory behind time series databases and learn practical methods for implementing them. Authors Ted Dunning and Ellen Friedman provide a detailed examination of open source tools such as OpenTSDB and new modifications that greatly speed up data ingestion. You'll learn: A variety of time series use cases The advantages of NoSQL databases for large-scale time series data NoSQL table design for high-performance time series databases The benefits and limitations of OpenTSDB How to access data in OpenTSDB using R, Go, and Ruby How time series databases contribute to practical machine learning projects How to handle the added complexity of geo-temporal data For advice on analyzing time series data, check out Practical Machine Learning: A New Look at Anomaly Detection, also from Ted Dunning and Ellen Friedman.

Temporal Data Mining

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Publisher : CRC Press
ISBN 13 : 1420089773
Total Pages : 398 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Temporal Data Mining by : Theophano Mitsa

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.

Sonification of Time Series Databases for Data Mining Tasks

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Publisher :
ISBN 13 :
Total Pages : 211 pages
Book Rating : 4.:/5 (129 download)

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Book Synopsis Sonification of Time Series Databases for Data Mining Tasks by : Anna Gorelik

Download or read book Sonification of Time Series Databases for Data Mining Tasks written by Anna Gorelik and published by . This book was released on 2008 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Time Series Databases

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Publisher :
ISBN 13 : 9781491920909
Total Pages : pages
Book Rating : 4.9/5 (29 download)

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Book Synopsis Time Series Databases by : Ted Dunning. Ellen Friedman

Download or read book Time Series Databases written by Ted Dunning. Ellen Friedman and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Foundations of Computational Intelligence

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Publisher : Springer
ISBN 13 : 3642010911
Total Pages : 397 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Foundations of Computational Intelligence by : Ajith Abraham

Download or read book Foundations of Computational Intelligence written by Ajith Abraham and published by Springer. This book was released on 2009-05-01 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundations of Computational Intelligence Volume 6: Data Mining: Theoretical Foundations and Applications Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, business, health care, banking, retail, and many others. Advanced representation schemes and computational intelligence techniques such as rough sets, neural networks; decision trees; fuzzy logic; evolutionary algorithms; arti- cial immune systems; swarm intelligence; reinforcement learning, association rule mining, Web intelligence paradigms etc. have proved valuable when they are - plied to Data Mining problems. Computational tools or solutions based on intel- gent systems are being used with great success in Data Mining applications. It is also observed that strong scientific advances have been made when issues from different research areas are integrated. This Volume comprises of 15 chapters including an overview chapter providing an up-to-date and state-of-the research on the applications of Computational Int- ligence techniques for Data Mining. The book is divided into 3 parts: Part-I: Data Click Streams and Temporal Data Mining Part-II: Text and Rule Mining Part-III: Applications Part I on Data Click Streams and Temporal Data Mining contains four chapters that describe several approaches in Data Click Streams and Temporal Data Mining.

Data Mining: Concepts and Techniques

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Publisher : Elsevier
ISBN 13 : 0123814804
Total Pages : 740 pages
Book Rating : 4.1/5 (238 download)

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Book Synopsis Data Mining: Concepts and Techniques by : Jiawei Han

Download or read book Data Mining: Concepts and Techniques written by Jiawei Han and published by Elsevier. This book was released on 2011-06-09 with total page 740 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data

Temporal and Spatio-Temporal Data Mining

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Publisher : IGI Global
ISBN 13 : 1599043890
Total Pages : 292 pages
Book Rating : 4.5/5 (99 download)

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Book Synopsis Temporal and Spatio-Temporal Data Mining by : Hsu, Wynne

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.

Principles of Data Mining

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Publisher : MIT Press
ISBN 13 : 9780262082907
Total Pages : 594 pages
Book Rating : 4.0/5 (829 download)

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Book Synopsis Principles of Data Mining by : David J. Hand

Download or read book Principles of Data Mining written by David J. Hand and published by MIT Press. This book was released on 2001-08-17 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. The growing interest in data mining is motivated by a common problem across disciplines: how does one store, access, model, and ultimately describe and understand very large data sets? Historically, different aspects of data mining have been addressed independently by different disciplines. This is the first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. The book consists of three sections. The first, foundations, provides a tutorial overview of the principles underlying data mining algorithms and their application. The presentation emphasizes intuition rather than rigor. The second section, data mining algorithms, shows how algorithms are constructed to solve specific problems in a principled manner. The algorithms covered include trees and rules for classification and regression, association rules, belief networks, classical statistical models, nonlinear models such as neural networks, and local "memory-based" models. The third section shows how all of the preceding analysis fits together when applied to real-world data mining problems. Topics include the role of metadata, how to handle missing data, and data preprocessing.

Traffic Monitoring and Analysis

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Publisher : Springer
ISBN 13 : 3642285341
Total Pages : 184 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Traffic Monitoring and Analysis by : Antonio Pescapè

Download or read book Traffic Monitoring and Analysis written by Antonio Pescapè and published by Springer. This book was released on 2012-03-07 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 4th International Workshop on Traffic Monitoring and Analysis, TMA 2012, held in Vienna, Austria, in March 2012. The thoroughly refereed 10 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 31 submissions. The contributions are organized in topical sections on traffic analysis and characterization: new results and improved measurement techniques; measurement for QoS, security and service level agreements; and tools for network measurement and experimentation.

Principles of Data Mining and Knowledge Discovery

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Publisher : Springer
ISBN 13 : 9783540632238
Total Pages : 404 pages
Book Rating : 4.6/5 (322 download)

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Book Synopsis Principles of Data Mining and Knowledge Discovery by : Jan Komorowski

Download or read book Principles of Data Mining and Knowledge Discovery written by Jan Komorowski and published by Springer. This book was released on 1997-06-13 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery, PKDD '97, held in Trondheim, Norway, in June 1997. The volume presents a total of 38 revised full papers together with abstracts of one invited talk and four tutorials. Among the topics covered are data and knowledge representation, statistical and probabilistic methods, logic-based approaches, man-machine interaction aspects, AI contributions, high performance computing support, machine learning, automated scientific discovery, quality assessment, and applications.

Periodic Pattern Mining

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Publisher : Springer Nature
ISBN 13 : 9811639647
Total Pages : 263 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Periodic Pattern Mining by : R. Uday Kiran

Download or read book Periodic Pattern Mining written by R. Uday Kiran and published by Springer Nature. This book was released on 2021-10-29 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to the field of periodic pattern mining, reviews state-of-the-art techniques, discusses recent advances, and reviews open-source software. Periodic pattern mining is a popular and emerging research area in the field of data mining. It involves discovering all regularly occurring patterns in temporal databases. One of the major applications of periodic pattern mining is the analysis of customer transaction databases to discover sets of items that have been regularly purchased by customers. Discovering such patterns has several implications for understanding the behavior of customers. Since the first work on periodic pattern mining, numerous studies have been published and great advances have been made in this field. The book consists of three main parts: introduction, algorithms, and applications. The first chapter is an introduction to pattern mining and periodic pattern mining. The concepts of periodicity, periodic support, search space exploration techniques, and pruning strategies are discussed. The main types of algorithms are also presented such as periodic-frequent pattern growth, partial periodic pattern-growth, and periodic high-utility itemset mining algorithm. Challenges and research opportunities are reviewed. The chapters that follow present state-of-the-art techniques for discovering periodic patterns in (1) transactional databases, (2) temporal databases, (3) quantitative temporal databases, and (4) big data. Then, the theory on concise representations of periodic patterns is presented, as well as hiding sensitive information using privacy-preserving data mining techniques. The book concludes with several applications of periodic pattern mining, including applications in air pollution data analytics, accident data analytics, and traffic congestion analytics.

Frequent Pattern Mining

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Publisher : Springer
ISBN 13 : 3319078216
Total Pages : 480 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Frequent Pattern Mining by : Charu C. Aggarwal

Download or read book Frequent Pattern Mining written by Charu C. Aggarwal and published by Springer. This book was released on 2014-08-29 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive reference consists of 18 chapters from prominent researchers in the field. Each chapter is self-contained, and synthesizes one aspect of frequent pattern mining. An emphasis is placed on simplifying the content, so that students and practitioners can benefit from the book. Each chapter contains a survey describing key research on the topic, a case study and future directions. Key topics include: Pattern Growth Methods, Frequent Pattern Mining in Data Streams, Mining Graph Patterns, Big Data Frequent Pattern Mining, Algorithms for Data Clustering and more. Advanced-level students in computer science, researchers and practitioners from industry will find this book an invaluable reference.

Mining Sequential Patterns from Large Data Sets

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Publisher : Springer Science & Business Media
ISBN 13 : 0387242473
Total Pages : 174 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Mining Sequential Patterns from Large Data Sets by : Wei Wang

Download or read book Mining Sequential Patterns from Large Data Sets written by Wei Wang and published by Springer Science & Business Media. This book was released on 2005-07-26 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: In many applications, e.g., bioinformatics, web access traces, system u- lization logs, etc., the data is naturally in the form of sequences. It has been of great interests to analyze the sequential data to find their inherent char- teristics. The sequential pattern is one of the most widely studied models to capture such characteristics. Examples of sequential patterns include but are not limited to protein sequence motifs and web page navigation traces. In this book, we focus on sequential pattern mining. To meet different needs of various applications, several models of sequential patterns have been proposed. We do not only study the mathematical definitions and application domains of these models, but also the algorithms on how to effectively and efficiently find these patterns. The objective of this book is to provide computer scientists and domain - perts such as life scientists with a set of tools in analyzing and understanding the nature of various sequences by : (1) identifying the specific model(s) of - quential patterns that are most suitable, and (2) providing an efficient algorithm for mining these patterns. Chapter 1 INTRODUCTION Data Mining is the process of extracting implicit knowledge and discovery of interesting characteristics and patterns that are not explicitly represented in the databases. The techniques can play an important role in understanding data and in capturing intrinsic relationships among data instances. Data mining has been an active research area in the past decade and has been proved to be very useful.