Temporal Data Mining
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,...
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| Main Author | |
|---|---|
| Format | eBook Book |
| Language | English |
| Published |
Boca Raton
Chapman and Hall/CRC
2010
Chapman & Hall/CRC CRC Press LLC Chapman & Hall |
| Edition | 1 |
| Series | Chapman & Hall/CRC data mining and knowledge discovery series |
| Subjects | |
| Online Access | Get full text |
| ISBN | 9781420089769 1420089765 1420089773 9781420089776 |
| DOI | 10.1201/9781420089776 |
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| Abstract | 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. |
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| AbstractList | 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. 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. Temporal data mining deals with the harvesting of useful information from temporal data. New initiatives in health care and business organizations have increased the importance of temporal information in data today.From basic data mining concepts to state-of-the-art advances, Temporal Data Mining covers the theory of this subject as well as its app |
| Author | Mitsa, Theophano |
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| Copyright | 2010 by Taylor and Francis Group, LLC Chapman & Hall/CRC is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S. Government works |
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| Keywords | Time Series Prediction Temporal Queries Gene Expression Time Series Data Data Sets DTW Spatiotemporal Data Mining Pattern Discovery Algorithms Execution Time Gps Trace Business Processes Gene Expression Time Series Financial Time Series Temporal Data Mining Web Usage Mining Apriori Algorithm TAs RFID Data Financial Time Series Forecasting Wavelet Transform Spatiotemporal Data Time Series Forecasting Embedding Dimension Time Series Classification Frequent Itemsets Temporal Databases |
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| Notes | Includes bibliographical references and index |
| OCLC | 610419386 |
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| PageCount | 398 |
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| Snippet | 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... Temporal data mining deals with the harvesting of useful information from temporal data. New initiatives in health care and business organizations have... |
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| SubjectTerms | Data mining Temporal databases |
| TableOfContents | Front cover -- Table of Contents -- Preface -- Chapter 1. Temporal Databases and Mediators -- Chapter 2. Temporal Data Similarity Computation, Representation, and Summarization -- Chapter 3. Temporal Data Classification and Clustering -- Chapter 4. Prediction -- Chapter 5. Temporal Pattern Discovery -- Chapter 6. Temporal Data Mining in Medicine and Bioinformatics -- Chapter 7. Temporal Data Mining and Forecasting in Business and Industrial Applications -- Chapter 8. Web Usage Mining -- Chapter 9. Spatiotemporal Data Mining -- Appendix A -- Appendix B -- Index -- Back cover |
| Title | Temporal Data Mining |
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