In contrast to traditional data mining methods, temporal data mining discovers dynamic knowledge related to activity, behavior, and evolution. This book presents the fundamentals of temporal data mining and its wide range of applications in medicine, finance, geographical information systems, and other areas. It covers essential data mining topics from the perspective of temporal data mining, addressing temporal databases and data models, temporal data representation and similarity computation, and temporal pattern detection. The author employs illustrative examples to explain key concepts and algorithms.…mehr
In contrast to traditional data mining methods, temporal data mining discovers dynamic knowledge related to activity, behavior, and evolution. This book presents the fundamentals of temporal data mining and its wide range of applications in medicine, finance, geographical information systems, and other areas. It covers essential data mining topics from the perspective of temporal data mining, addressing temporal databases and data models, temporal data representation and similarity computation, and temporal pattern detection. The author employs illustrative examples to explain key concepts and algorithms.
Theophano Mitsa, Ph.D., is a software consultant and electrical engineer with expertise in image analysis, computer vision, machine learning, pattern recognition, medical informatics, and decision support systems.
Inhaltsangabe
Temporal Databases and Mediators. Temporal Data Similarity Computation, Representation, and Summarization. Temporal Data Classification and Clustering. Prediction. Temporal Pattern Discovery. Temporal Data Mining in Medicine and Bioinformatics. Temporal Data Mining and Forecasting in Business and Industrial Applications. Web Usage Mining. Spatiotemporal Data Mining. Appendices. Index.
Temporal Databases and Mediators. Temporal Data Similarity Computation, Representation, and Summarization. Temporal Data Classification and Clustering. Prediction. Temporal Pattern Discovery. Temporal Data Mining in Medicine and Bioinformatics. Temporal Data Mining and Forecasting in Business and Industrial Applications. Web Usage Mining. Spatiotemporal Data Mining. Appendices. Index.
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