Data Mining in Time Series Databases Mark Last

ISBN: 9789812382900

Published: June 25th 2004

Hardcover

192 pages


Description

Data Mining in Time Series Databases  by  Mark Last

Data Mining in Time Series Databases by Mark Last
June 25th 2004 | Hardcover | PDF, EPUB, FB2, DjVu, audiobook, mp3, ZIP | 192 pages | ISBN: 9789812382900 | 5.53 Mb

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 seriesMoreAdding 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.



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