Mining Sequential Patterns from Large Da

Forfattere

Kort om boken

In many applications, e.g., bioinformatics, web access traces, system u- lization logs, etc., the data is naturally in the form of sequences. It has been of great interests to analyze the sequential data to find their inherent char- teristics. The s…
839,-
1049,-
Spar 210,-
Format/språk
Format
Forklaring av formater
  • Innbundet

    Bok med hardt omslag.

  • Pocket

    Heftet bok med mykt omslag.

  • Kartonert

    Bok med tykke, stive sider.

  • E-Bok

    Digitalt format. E-bok kan leses i ARK-appen eller på Kindle. Bøkene kan også lastes ned fra Din side.

  • Nedlastbar lydbok

    Digitalt format. Nedlastbar lydbok kan lyttes til i ARK-appen. Bøkene kan også lastes ned fra Din side.

  • Digikort lydbok

    Lydbok på digikort. Krever Digispiller.

  • Compact Disc

    Lydbok eller musikk på CD. Krever CD-spiller eller annen kompatibel avspiller.

  • Vinyl

    Vinylplate. Krever platespiller.

  • DVD

    DVD-film. Krever DVD-spiller eller annen kompatibel avspiller.

  • Blu-ray

    Blu-ray-film. Krever Blu-ray-spiller eller annen kompatibel avspiller.

    Om Mining Sequential Patterns from Large Da

    In many applications, e.g., bioinformatics, web access traces, system u- lization logs, etc., the data is naturally in the form of sequences. It has been of great interests to analyze the sequential data to find their inherent char- teristics. The sequential pattern is one of the most widely studied models to capture such characteristics. Examples of sequential patterns include but are not limited to protein sequence motifs and web page navigation traces. In this book, we focus on sequential pattern mining. To meet different needs of various applications, several models of sequential patterns have been proposed. We do not only study the mathematical definitions and application domains of these models, but also the algorithms on how to effectively and efficiently find these patterns. The objective of this book is to provide computer scientists and domain - perts such as life scientists with a set of tools in analyzing and understanding the nature of various sequences by : (1) identifying the specific model(s) of - quential patterns that are most suitable, and (2) providing an efficient algorithm for mining these patterns. Chapter 1 INTRODUCTION Data Mining is the process of extracting implicit knowledge and discovery of interesting characteristics and patterns that are not explicitly represented in the databases. The techniques can play an important role in understanding data and in capturing intrinsic relationships among data instances. Data mining has been an active research area in the past decade and has been proved to be very useful.

    Kundevurderinger

    Totalvurdering: 

    Gi din vurdering: 
    Totalvurdering: 

    Detaljer

    Format
    E-Bok
    Kopisperre
    Teknisk DRM
    Filformat
    PDF
    Utgivelsesår
    2006
    Forlag
    Springer US
    Språk
    Engelsk
    ISBN
    9780387242477

    Anbefalt

    Anbefalt