Sequence Data Mining
indgår i Advances in Database Systems serien
- Indbinding:
- Hardback
- Sideantal:
- 150
- Udgivet:
- 9. august 2007
- Udgave:
- 2007
- Størrelse:
- 156x11x234 mm.
- Vægt:
- 413 g.
- 8-11 hverdage.
- 19. februar 2025
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- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
Beskrivelse af Sequence Data Mining
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.
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.
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