£73.08

Springer Mining Sequential Patterns from Large Data Sets: 28 (Advances in Database Systems, 28)

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Description

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.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
06 December 2010
Listed Since
06 July 2010

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