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Link Mining: Models, Algorithms, and Applications pp 107–133Cite as

A Survey of Link Mining Tasks for Analyzing Noisy and Incomplete Networks

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Abstract

Many data sets of interest today are best described as networks or graphs of interlinked entities. Examples include Web and text collections, social networks and social media sites, information, transaction and communication networks, and all manner of scientific networks, including biological networks. Unfortunately, often the data collection and extraction process for gathering these network data sets is imprecise, noisy, and/or incomplete. In this chapter, we review a collection of link mining algorithms that are well suited to analyzing and making inferences about networks, especially in the case where the data is noisy or missing.

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Acknowledgments

The work was supported by NSF Grant #0746930.

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  1. Department of Computer Science, University of Maryland, College Park, MD, USA

    Galileo Mark Namata, Hossam Sharara & Lise Getoor

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  1. Galileo Mark Namata
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Correspondence to Lise Getoor .

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  1. Dept. Computer Science, University of Illinois, Chicago, S. Morgan St. 851, Chicago, 60607-7053, Illinois, USA

    Philip S. Yu

  2. Dept. Computer Science, University of Illinois, Urbana-Champaign, N. Goodwin Ave. 201, Urbana, 61801, Illinois, USA

    Jiawei Han

  3. School of Computer Science, Carnegie Mellon University, Forbes Ave. 5000, Pittsburgh, 15213, Pennsylvania, USA

    Christos Faloutsos

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Namata, G.M., Sharara, H., Getoor, L. (2010). A Survey of Link Mining Tasks for Analyzing Noisy and Incomplete Networks. In: Yu, P., Han, J., Faloutsos, C. (eds) Link Mining: Models, Algorithms, and Applications. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-6515-8_4

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