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A Survey of Graph Mining for Web Applications

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Managing and Mining Graph Data

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

Abstract

Graph structures provide a general framework for modeling entities and their relationships, and they are routinely used to describe a wide variety of data such as the Internet, the web, social networks, metabolic networks, protein-interaction networks, food webs, citation networks, and many more. In recent years, there has been an increasing amount of literature on studying properties, models, and algorithms for graph data. In this chapter we provide a brief overview of graph- mining algorithms for web and social-media applications. We review a wide range of algorithms, such as those for estimating reputation and popularity of items in a network, mining query logs and performing query recommendations. The main goal of the chapter is to provide the reader with an understanding of how graph structural mining algorithms can be exploited in the context of web applications. This highlights the challenges of, and provides an understanding of the power of graph mining in the context of web and social-media applications.

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Author information

Authors and Affiliations

  1. Yahoo Research, Avd Diagonal 177, Barcelona, Spain

    Debora Donato & Aristides Gionis

Authors
  1. Debora Donato
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  2. Aristides Gionis
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Corresponding author

Correspondence to Debora Donato .

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Editors and Affiliations

  1. Thomas J. Watson Research Center, IBM, Skyline Drive 19, Hawthorne, 10532, U.S.A.

    Charu C. Aggarwal

  2. Microsoft Research Asia, Zhichun Road 49, Beijing, 100080, China, People's Republic

    Haixun Wang

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Donato, D., Gionis, A. (2010). A Survey of Graph Mining for Web 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_15

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  • DOI: https://doi.org/10.1007/978-1-4419-6045-0_15

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