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Mining Sequential Patterns from Large Data Sets
Paperback
Series: Advances in Database Systems, Book 28
DatabasesGeneral ComputersSystem Administration
ISBN13: 9781441937070
Publisher: Springer Nature
Published: Dec 6 2010
Pages: 163
Weight: 0.57
Height: 0.38 Width: 6.14 Depth: 9.21
Language: English
In many applications, such as bioinformatics, web access traces, and system utilization logs, the data is naturally in the form of sequences. Examples of sequential patterns include but are not limited to protein sequence motifs and web page navigation traces. To meet the different needs of various applications, several models of sequential patterns have been proposed. This volume not only studies the mathematical definitions and application domains of these models, but also the algorithms on how to effectively and efficiently find these patterns. It provides a set of tools for analyzing and understanding the nature of various sequences by identifying the specific model(s) of sequential patterns that are most suitable.
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