Sequence Data Mining Sequence Data Mining

Sequence Data Mining

    • 109,99 €
    • 109,99 €

Beschreibung des Verlags

Understanding sequence data, and the ability to utilize this hidden knowledge, creates a significant impact on many aspects of our society. Examples of sequence data include DNA, protein, customer purchase history, web surfing history, and more.


Sequence Data Mining provides balanced coverage of the existing results on sequence data mining, as well as pattern types and associated pattern mining methods. While there are several books on data mining and sequence data analysis, currently there are no books that balance both of these topics. This professional volume fills in the gap, allowing readers to access state-of-the-art results in one place.


Sequence Data Mining is designed for professionals working in bioinformatics, genomics, web services, and financial data analysis. This book is also suitable for advanced-level students in computer science and bioengineering.

Forward by Professor Jiawei Han, University of Illinois at Urbana-Champaign.

GENRE
Computer und Internet
ERSCHIENEN
2007
31. Oktober
SPRACHE
EN
Englisch
UMFANG
166
Seiten
VERLAG
Springer US
ANBIETERINFO
Springer Science & Business Media LLC
GRÖSSE
2
 MB
Mining Sequential Patterns from Large Data Sets Mining Sequential Patterns from Large Data Sets
2006
Knowledge Discovery in Inductive Databases Knowledge Discovery in Inductive Databases
2007
Periodic Pattern Mining Periodic Pattern Mining
2021
Compression Schemes for Mining Large Datasets Compression Schemes for Mining Large Datasets
2013
Algorithms and Applications Algorithms and Applications
2010
From Sequences to Graphs From Sequences to Graphs
2022
Feature Engineering for Machine Learning and Data Analytics Feature Engineering for Machine Learning and Data Analytics
2018
Advances in Data and Web Management Advances in Data and Web Management
2007