Mining Sequential Patterns from Large

Description

The focus of Mining Sequential Patterns from Large Data Sets is on sequential pattern mining. In many applications, such as bioinformatics, web access traces, system utilization logs, etc., the data is naturally in the form of sequences. This information has been of great interest for analyzing the sequential data to find its inherent characteristics. 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.

Mining Sequential Patterns from Large Data Sets 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. This book provides an efficient algorithm for mining these patterns.

Mining Sequential Patterns from Large Data Sets is designed for a professional audience of researchers and practitioners in industry, and also suitable for graduate-level students in computer science.



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1. Ebooks list page : 1131
2. Mining Sequential Patterns from Large
3. Mining Sequential Patterns from Large Data Sets (Advances in Database Systems)
4. Large-Scale Parallel Data Mining
5. Data Mining Patterns: New Methods and Applications
6. Data Mining Patterns: New Methods and Applications
7. Data Mining Patterns: New Methods and Applications
8. Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage
9. Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage
10. Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage
11. Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage
12. Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage
13. Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage (Repost)
14. Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage (Repost)
15. Lyle.Lovett.And.His.Large.BandIts.Not.Big.Its.Large
16. Sequential Analysis