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Graph Data Management and Mining: A Survey of Algorithms and Applications

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Managing and Mining Graph Data

Part of the book series: Advances in Database Systems ((ADBS,volume 40))

Abstract

Graph mining and management has become a popular area of research in recent years because of its numerous applications in a wide variety of practical fields, including computational biology, software bug localization and computer networking. Different applications result in graphs of different sizes and com- plexities. Correspondingly, the applications have different requirements for the underlying mining algorithms. In this chapter, we will provide a survey of dif- ferent kinds of graph mining and management algorithms. We will also discuss a number of applications, which are dependent upon graph representations. We will discuss how the different graph mining algorithms can be adapted for different applications. Finally, we will discuss important avenues of future research in the area.

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    Charu C. Aggarwal

  2. Microsoft Research Asia, Beijing, China, 100190

    Haixun Wang

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    Charu C. Aggarwal

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    Haixun Wang

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Aggarwal, C.C., Wang, H. (2010). Graph Data Management and Mining: A Survey of Algorithms and Applications. In: Aggarwal, C., Wang, H. (eds) Managing and Mining Graph Data. Advances in Database Systems, vol 40. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-6045-0_2

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